Chi-square test is the commonly applied test of statistical significance and for the measures of correlation, the contingency coefficient can be worked out.The scale does not exhibit any order or distance relationship and also does not have an arithmetical origin.This scale is not of much use in determining relationships, but finds uses in preliminary exploratory work aimed at knowing the broad dimensions of a certain phenomenon. Ordinal ScalesAn ordinal scale contains categories that can be ordered by rank on a continuum. These are thus ranking scales. Besides having the characteristics of the nominal scale, the scale has the characteristics of the categories having rudimentary arithmetic meaning such as ‘more’; or ‘less’ of the quantity being measured.How much knowledge do you have about the Internet?

• No knowledge- 0 • Little knowledge- 1 • Moderate knowledge- 2

Expert level knowledge- 3An ordinal scale provides only much information about the level of web awareness tells us nothing about the distance between the point values. The interval between 0 and 1 may be larger or smaller does not imply anything about the arithmetic values other than that they are in specific order.CEAT Cricket ratings ( for the week ended xxxx )Rank Name of the Country Points1 Australia 692 India 54 3 South Africa 524 Pakistan 43 The ordinal scale is used when one is able to distinguish between two objects based on a particular attribute. The ordinal scale is frequently used in relation to study of qualitative phenomena.One must be very careful while making any statement in relation to the ordinal scales. In the CEAT cricket ratings example above, Australia is ranked 1 and India 2. Does it mean that Australia is twice as better as India? ( the scores tells us that it is not so ). Ordinal scales only rank items as per their order given and have no absolute value. The real difference between adjacent ranks may no be the same. One can only say that a team is up or down on the rating scale. One cannot make any more precise comments that this. Simply put, an ordinal scale deals with possibly one of the three relations, greater than less than and equal to.Interval ScalesWhen the numbers attached to a variable imply not only that 50 is greater than 40 and 40 is greater than 30, but also that the size of the interval between 50 and 40 is the same as that between 40 and 30, then such a scale is called as an interval scale. An interval scale has the power of determining equality of differences.Just because a scale has values from 1 to 100, it does not automatically mean that the difference between a score of 30 and 40 is the same that between 90 and 100. Consider the use of such a 100-point scale in a software proficiency test. The difference between scores of 90 and 100 perhaps signifies a greater difference in software proficiency than

between scores of 30 and 40. Every increase/ decrease in the scale there is a corresponding unit increase/decrease in the variable being measured. The classic example of this is the Fahrenheit scale of temperature. The difference between 30 and 31 degree Fahrenheit is the same as that between 38 and 39 degree Fahrenheit.Ratio ScaleRatios scales have a true zero and therefore the values on such a scale can be multiplied or divided. The simplest examples are the scales for measuring length (meter scale), weight (kilogram scale) etc . 2 meters is exactly half that of four meters and exactly twice of 1 meter. One can convert numbers from one scale to another scale in this case (meter to feet, kilos to pounds). Although we cannot point to an object of 0 meter length, on the scale we do have a definite zero. Some scales used in social research seem to be deceptively similar to ratio scales. For e.g. suppose we use monthly family income as an indicator of social status. The status difference between the monthly family incomes of 5000 and 30000 is surely far greater than that between 1,50,000 and 1,75,000. The difference of Rs. 25,000 will be less and less significant as we move up the ladder. Consider a scale that uses money as a measure of social status. A person X can possess absolutely no money. Does it imply that he has no social status? Not exactly.Scale Construction TechniquesThe following are the main techniques by which scales can be developed.Arbitrary approach : In this method the scale is developed on an adhoc basis. This is the most widely used approach. The assumption is that such a scale measures the construct for which the scale is devised.Consensus approach : The items drafted for inclusion in the instrument are selected by a panel of experts, based on their judgment of the relevance and use of every item and its contribution towards the desired measurement.Item analysis approach : A group of respondents is made to answer a battery of test items developed into a comprehensive test. The total scores are calculated for every individual and individual items are then analyzed to determine the items that discriminate between study objects with high scores and those with low scores.Cumulative scales approach : In this approach cumulative scales are chosen on the basis of their conforming to some ranking of items with ascending and descending discriminating power.Factor scales approach : The scale is constructed on the basis of inter-correlations of items that indicate a common factor accounts for the relationship between items. The relationship is measured by applications of factor analysis. Rating ScalesThe scale measures an attribute by judgment on a continuum. The object is judged in obsolete terms against some specified criteria i.e. without reference to other similar objects.The ratings are in the form of “like – dislike”, “satisfied – dissatisfied”.The number of facts are not fixed by any rule.3 point to 7 point scale are more common one.Rating scales are three typesThe graphic rating scale.Itemized (numerical) rating scale.Verbal rating scale.

Graphic rating scaleIt employs a line that has at its two extremes marked the extreme values of the attributes being measured.Scale points are also indicated at intermediate points along the line to help the rater ascertain his position.The rater has to put a tick mark at a point on the line to indicate his position with respect to the attribute being measured.Advantages : Easy to understand. Simple to use. Flexible in the sense that it enables finer distinctions of degree.Disadvantages : respondents may tick arbitrarily. Respondents frame of reference plays an important role in understanding the terms.

Itemized rating scaleConsists of a series of short statements on a specific issue or topic and the respondent has to chose one of these to indicate his position with respect to the issue or topic being investigated.The items (statements) are arranged in an ascending or descending order of the attribute or characteristic of interest. Scales with five or seven categories are the norm, however, we also find scales with as many as eleven categories.How often do you report late to office?I always report late to office.I report late to office, most of the times.I report late to office, some of the time.I rarely report late to office.I never report late to office.This scale provides more meaningful information to the rater, and therefore is more reliable. The statements that form the scale are often difficult to develop. The subject want to say something different.Ranking scalesIn this type of scales the rater judges each item in comparison to similar items and arrives at his judgment. A ranking scale ranks objects or persons in order from the most to least of the attribute of interest. Two or more objects are directly compared and a choice is made among them.Ranking scales are of the following types Simple rankingMethod of paired comparisonMethod of rank order Simple or straight ranking : in this method the respondents are asked to rank their choices as 1,2,3A housewife – respondent may be requested to list the attributes she thinks are important in making the choice of a washing machine.Attribute Rank

ExtremelyDissatisfied

ExtremelySatisfied

Durability …….Brand name …1..Maintenance costs …….Cost …….Cleaning Time …2...Quality of Cleaning …3...Ease of operation …….Every rank may be given a score corresponding to its position, higher the rank higher will be the scored assigned.For example, if in the above question there are 10 possible ranks, the item ranked 1 will have a score of 10, the item ranked 2 will have score as 9, and so on, till we reach score 1 for the item ranked 10th.The rank scores are then multiplied their frequencies and the total score for each item on the scale is arrived at.

Attributes 1st 2nd 3rd Total

Durability 20*3 20*2 10*1 110

Brand Name 35*3 10*2 5*1 130

Cost 25*3 15*2 10*1 115Method of Paired comparison : In this method, the respondents are presented some stimuli in pairs and they are asked to select the preferred one or the better one in every case.Suppose a business magazine invites 100 share brokers to identify the best industries for investment in the stock-markets. Lets say the research bureau of the magazine has already shortlisted five industries – automobiles, biotechnology, cement, software and FMCG.Ten Pairs will be formed out of the five industries such asAutomobiles SoftwareCement Automobile FMCG BiotechnologyAutomobile FMCGBiotechnology AutomobileSoftware CementBiotechnology SoftwareCement BiotechnologySoftware FMCGFMCG CementEach industry appears only once in every pair and it appears first in a pair as many times as it appears second.

  Automobiles Biotechnology Cement

Software Automobile … 82 69 25 Biotechnology 18 … 27 7

Cement 31 73 … 16 Software 75 93 84 …

FMCG 65 85 75 41

Total 189 333 255 89

Rank Order 3 1 2 5There is consistency in responses. If biotechnology scores favorable as compared to automobiles, and automobiles compares favorable to FMCG, the biotechnology compares favorably to FMCG.The disadvantage of the paired comparison method lies in the fact that the number of comparisons is too large for increased number of stimuli, and the rater may lose his interest in the act.Method of ranked order : Here the rater is required to rank his choices. It is easier and faster than the earlier paired comparison method. For ten stimuli used in the earlier case of paired comparison, the number of comparisons are 10(9) / 2 = 45, where as in this method the rater has to rank only ten items. Usually we are interested in the initial first three – five scores only and therefore at times the rater need not rank all the items in the stimuli.Attitude ScalesThese are short but carefully drafted statements (attitude statements0 or propositions that deal with several selected aspects or with many appropriate aspects of the attitude object (issue, individual, organization, concept etc.)These are crude indicators of attitude. The major types of attitude scales are …Thurstone ScaleLikert ScaleGuttman ScaleSemantic differential scale.Differential Scales – Thurstone ScalesIn this type of scales, a large number of items are created and a panel of judges is asked to evaluate the items and determine their relevance to the topic area, clarity and degree of favorableness towards the objects. The attitudes are represented in the form of a frequency distribution, with the base line indicating the whole range of attitudes from the most favourable at one end, to the least at the other, with a neutral zone in between.Steps in constructing a Thurstone attitude scaleStep 1 : The statements must cover the entire range of attitudes from most favorable to the most unfavorable, including an adequate number of neutral statements. There is no rule about the number of statements. The statements should be brief, unambiguous and

relevant and be worded in such a way that they can be approved or disapproved in terms of a definitely expressed attitude.Step 2 : After careful editing the statements are arbitrarily assigned numbers for the purpose of identification and mimeographed in such a form that they can be cut into fairly uniform individual slips of paper. Complete sets of the statements are given to a large number of judges with clear, simple instructions to sort piles represent a graduated series of attitudes from the most favorable to the least favorable.Step 3 : After the sorting process is over for all the judges, a tabulation is prepared to determine the number of times a statement had fallen into a particular pile.Step 4 : The scale values for each statement are determined graphically. The accumulated proportions of each statement are plotted in the form of an ogive or a cumulative frequency curve.Step 5 : the final scale consists of about 15 to 20 comparatively unambiguous, relevant statements arranged randomly, representing a graded series of values ranging from the most favorable to the least favorable. The scale is now ready for administration to a sample of respondents of which the attitude is to be measured.Step 6 : Two alternative scoring procedures either ( a ) the arithmetic mean of the scale values of the statements that are indorsed, or ( b ) the median values of the indorsed statements, indicated by either a single or a double check.Advantages of the Thurstone ScaleThe is simple to administer.It is appropriate and reliable for measuring a single attitude.The scales values with different sets of judges highly correlate witheach other, provided that judges with extreme opinions or views are excluded. It is advisable to use judges with similar profiles as that of the respondents. Limitations of the Thurstone Scale

1. It is time consuming to construct. It involves a lot of cost and effort.2. It involves dealing with equal-appearing intervals and not with equal intervals. The term

appearing refers to only a psychological existence and not to numerical existence.3. There is a likelihood that the same total score obtained by different persons may express

different attitudinal patterns.4. The scale cannot be applied to measure a complex of attitudes.

The method involves subjective elements.The Summated Rating Scale – The Likert ScaleA particular item is evaluated on the basis of how well it discriminates between those persons whose total score is high and whose total score is low. A summated scale consists of a series of statements to which the subject is asked to react. The scale consists of only those statements that seem to be definitely favorable or definitely unfavorable to the issue. The subject expresses his agreement/disagreement and its degree with each scale item. Every response is assigned a numerical value based upon the degree of favorableness / unfavourableness. Summing up his responses to each of the constituent statements given the total score of an individual.Likert scale is by far most the popular of all measurement scales. It is meant for measuring ordinal attributes like attitudes. It is designed to measure the intensity with which an attitude is expressed.

The respondent is asked to respond to each of the statements in terms of several degrees of agreement or disagreement. The following five point constitute the scale

Position Score Score

Strongly approve +2 5

Approve +1 4

Undecided 0 3

Disapprove -1 2

Strongly disapprove -2 1

The number of categories or degrees used is usually five, but may be three or even seven.Steps in constructing a Likert ScaleStep 1 : The statements are selected with an emphasis on values rather than on facts. The statements are so worded as to indicate a clear position for or against the point. Step 2 : The weights assigns are 5,4,3,2,1, or 1,2,3,4,5, in the order appropriate to the degree of favorableness or unfavourableness. Step 3 : A large number of respondents are requested to check their responses (attitudes) on the list of statements in accordance with the scheme outlined in the step 2.Step 4 : A total score for every subject or respondent is obtained by summing the values of each item that is checked.Step 5 : The two extreme groups of top 25% and the bottom 25% represent the most favorable and the least favorable statements and are generally included in the final scale.Step 6 : Another way to carry out an item analysis to decide which are the best statements for inclusion in the final scale, is to calculate the correlation coefficient for each item with the total score (minus the score of the items in question). Only items with highest correlations are retained. This method is called as the internal consistency method of analysis.Advantages of the Likert Scale

1. Simple to construct2. It permits the expression of several degrees (usually five) on the continuum of agree-

disagree and thus is likely to be more reliable than two-point scale with only the two extremes being specified.

3. It provides more precise information about the subject’s position on the issue.4. The scale is unidimensional, i.e. a;; items measure the same thing.5. The scale is flexible in the sense that one can have as many or as few items in the scale.6. The scale does not call for any expert opinion.7. The scale can be used in respondent-centeres studies (how responses differ between

people) as well as in stimulus-centered studies (how responses differ between stimuli). Limitations of the Likert Scale

1. It only tells us whether respondents are more or less favorable to an issue, but not how much more or less. The scale does not have a neutral point.

2. Often the total score of an individual has little clear meaning since the total score can be secured by a variety of answer patterns. Thus, there is lack of reproducibility, and two or more identical scores may have different implications.

3. Respondents may answer according to what they should feel rather than how do they feel.

4. The assumptions that all items in the Likert Scale have equal weights may be erroneous. Certain statements compared with others may have greater meaning to a person.It is highly reliable for rough ordering of people with regards to a particular attitude.Cumulative Scales – Guttman Scale (Scalogram)The scale has a series of statements to which the respondent expresses his agreement or disagreement. The cumulative scales have special characteristics that statements in it form a cumulative scale. The statements are related to each other in such a fashion that a respondent who agrees to item number 4 also responds favorably to items 3,2,1 and a respondent who responds favorably to item number 3 will also respond favorably to items 2,1. The major scale of this type of scale is the Guttman Scale or Scalogram. The population of objects refers to the class of objects that are defined as the subjects for the study in question. The universe of attributes refers to a class of qualitative variables associated with these objects that is defined for study. These variables may be any type of qualitative variables and need not necessarily be related to attributes.Gutman and his peers developed four specific techniques for scale analysis, all of which produce essentially the same results, but differ in the mechanics involved. The most popular of these methods is the Cornell technique and is the simplest to apply.Advantages of scalogram technique

1. The scale enables one-dimensional measurement.2. Researcher’s subjective judgment has no say, as the scale is prepared by using the replies

of the respondents.3. A respondent’s response pattern can be reproduced given his total score on the scale.4. The scale can be easily administered, as only a small number of items are required.5. It can be applied to personal, telephonic, or mail survey.

Limitations of scalogram technique1. Scales are relative to time and to population. A universe may scalable at one time but not

at another. It may be scalable at two different periods of time but with different orders objects and categories.

2. The criterion of reproducibility is arbitrarily fixed at 0.9. 3. The criterion of reproducibility is an useful but not an essential property.

Factor Scale – Semantic differential ScaleFactor scaling is a technique developed to identify and study the multidimensional complex attitudes. These scales are developed by the application of factor analysis, or on the basis of inter-correlations of items that indicate that a common factor accounts for the relationships between them.Factor analysis specifically aims to resolve two issues

• How to deal appropriately with the universe of content which is multidimensional? • How to uncover underlying (latent) dimensions which have not been identified?

There are three types of factors 1. A general factor that contributes to all the items in the scale. 2. A group factor that contributes to more than two but not all the items in the scale.

A specific factor that contributes to on more than one item of the scale.Two widely used scales based on the concepts of factor analysis are The semantic differential scaleMultidimensional scaling.

Semantic differential scale : it attempts to measure the psychological meanings of an object to an individual. The scale is based on the proposition that an object has multidimensional connotative meanings that can be located in a multidimensional property space called as the semantic space. The scale consists of a set of bipolar rating scales, usually of 7 points. Respondents use this 7 point scale to rate one or more concepts, relevant to the subject matter of study on each scale item.For e.g. to study desirable attributes of a two-wheeler, the scale items can be

Fuel Efficient

--- --- --- --- --- --- ---

Inefficient

Sturdy --- --- --- --- --- --- ---

Shaky

Attractive --- --- --- --- --- --- ---

Dull

Cheap --- --- --- --- --- --- ---

Costly

Trendy --- --- --- --- --- --- ---

Conventional

Comfortable --- --- --- --- --- --- ---

Uncomfortable

Heavy --- --- --- --- --- --- ---

Light

+3 +2 +1 0 -1 -2 -3

After a lot of research it was found out that three factors ultimately contributed the most of meaningful judgments by the respondents – Evaluation, Potency and Activity Evaluation Potency Activity

Good – bad Large – small Active – passive

Positive – negative Hard – soft Fast – slow

Clean - dirty Strong - weak Hot - cold

Steps in construction of a semantic differential scaleStep 1 – select the concepts to be studied in terms of the nature of the research problem.Step 2 – scales should be stable across subjects and concepts, also they should be linear between polar opposites.Step 3 – a panel of experts is employed to rate the various stimuli (or objects) on the various selected scales and the responses are pooled to determine the composite rating.Step 4 – the scores are assigned from 1 to 7 (weak – strong) or from 7 to 1 (strong – weak) based on the order of the adjectives.Step 5 – a respondent’s total score is a measure of his attitude. Thus semantic differential scale is summated rating scale.Applications of the semantic differential scaleIt is widely used in brand image and other marketing studies, institutional images, political issues, personality studies, study of emotions, attitude measurement and value studies.

Multidimensional scaling It is basically a data reduction technique. The primary purpose is to uncover the hidden structure of a set of data. It enables to represent the proximity between objects spatially as in a map.MDS is used when all the variables in a study are independent of each other and are to be analyzed simultaneously (multivariate analysis). It is widely used in marketing research.Two approaches are popular in the context of MSD – the metric approach and the non-metric approach.Significance : it enables the researcher to study the perceptual structure of a set of stimuli and the cognitive processes underlying the development of this structure. The technique does away with the need in data collection process to specify the attributes along which several objects (brands, products) may be compared. The MDS technique is a great advance over unidimensional measurement.Limitation : MDS is not widely used because of the complex computations involved. The method is laborious and difficult to comprehend.Methods of data collectionData are facts, figures, symbols and other relevant material, past and present, serving as bases for study and analysis.Observations dies not merely imply the sense of vision, but relates to all forms of perception used in recording responses as they impinge upon us. If either of our senses does not perceive any event or phenomena, there is no data. Thus response does not constitute data, it is the recording of this response that constitute data.Stimulus à Response à recording of response (data) Responses Stimuli

Unstructured Structured

Unstructured Informal settings Formal unstructured settings

Structured impossible Formal structured settings

One cannot draw inferences without analyzing data. The relevance, adequacy and reliability of data determine the quality of the study. Data form the basis of hypothesis testing. They are the basic input for constructing measurement scales. The entire scientific process of measurement, analysis, testing and inferences depends upon the availability of relevant and accurate data.Data is primarily of two kindsPrimary DataSecondary DataSecondary data : it is defined as data that has been collected earlier for some purpose other than the purpose of the present study. Any data that is available prior to the

commencement of the research project is secondary data, and therefore secondary data is also called as historical data.It provides wealth of information to the researcher.It often obviates the need of primary data collection and saves valuable time, effort and money. Even where subsequent primary data collection is required, an analysis of secondary data enlightens the researcher regarding many aspects of the study and gives contextual familiarity for primary data collection. It thus provides rich insights into the research process.Uses of secondary data

1. It acts as reference for the present study. 2. It is a useful benchmark against with the findings of the study can be tested.

At times it may be the only source of data.Sources of secondary dataPublished sourcesUnpublished sourcesPublished sources : Government sources.

1. Census report2. Publications of planning commission3. Reports of statistical information4. Reports of government departments5. Annual reports, Bulletin of RBI6. Central statistical organization reports7. Annual survey of industries8. Reports published by NABARD, NCAER, FICCI, ASSOCHAM, CII.

Non Governmental Sources1. Annual and financial reports of companies2. Publications of international organizations such as UN, WTO, World bank, IMF etc.3. Publications of commodity boards – milk, sugar, cotton, coffee etc.4. Stock exchange directories5. Trade and financial journals6. National readership surveys7. Syndicated services that provide marketing related information – retail audits, industry

specific reports.8. TRP (Television rating points) surveys9. Books, newspapers and magazines.10. Reports prepared by research scholars, economist etc.

Unpublished sources of secondary data1. Letters2. Diaries3. Biographies & autobiographies4. Accounting and financial records5. Register of members6. Minutes of meetings7. Inventory records

8.Personal recordsAdvantages of secondary data

1. The cost of data collection is lower.2. Offer enough insight and information.3. Helps to uncover new ideas for hypothesis formulation.4. Help the researcher to understand the possible improvements required in the research

design, data analysis plan.5. Can be a useful reference base for comparison of research findings.6. Time involved in collecting secondary data is less.7. Provides additional empirical support to the findings.8. Helps to cover wide geographical areas and longer time span cheaply.

Only method for studying the past.Limitations of Secondary Data

1. It is never safe to take published statistics at their face value.2. The classification bases used in the secondary data often do not coincide with those of the

present study. E.g. present study may classify companies based on assets as a measure of size, while the past data may have listings based on turnover as a measure of size.

3. Categorization mismatching – secondary data may classify 18 years and above as adults, where as the researcher may have used 21 years and above as level of classification.

4. It is not enough to know what was the purpose behind the data collection, it also necessary to know how the data was collected.

5. At times secondary sources do not explicitly define the terms of reference of the study, the objectives and methodology adopted.

6. Locating appropriate sources of secondary data is tedious.7. It suffers from a major limitation of obsolescence8. One cannot be always sue of the accuracy of secondary data.9. Data may be available but not always accessible, as in case of propriety data.

Evaluation of secondary data

Reliability – whether the data are dependable.

Suitability – whether the data can be applied successfully in the present situation.

Adequacy – whether the level of accuracy of secondary data is adequate for meeting the needs of the present study.

Primary Data

Data that is collected for specific purpose at hand is called as primary data. The collection of primary data is costly and time consuming. It calls for greater planning and coordination. Collection of primary data requires deploying more man power.

Methods of primary data collection can be classified under two basic heads –

The Questionnaire Method – the respondent is questioned directly about aspects of interest to the researcher.

The Observation Method – the researcher simply observes the subject and records relevant aspects of his behavior.

Data collection methods can be classified as:

Observation.

Interviewing.

Experimentation.

Simulation.

Projective techniques.

Observation

The observation method is a commonly used method in social sciences. In this method, instead of questioning the respondent, the researcher observes the subject and records relevant behaviour. Observation may be defined as a systematic viewing of phenomenon in its proper setting for the specific purpose of gathering data for a particular study.

Usually one observes the current happenings, but past happenings can be observed by inference i.e. by looking at the results of such past phenomenon. Observation is both a physical and mental activity. It is selective and purposive. E.g. the researcher may personally visit ‘pan’ outlets and observe the teenagers hanging out over there, or he may study (observe) the garbage at various localities and record the number of empty cigarette packs thrown away.

Observation becomes scientific when it :

1. Serves a formulated research problem,

2. Is planned deliberately,

3. Is recorded systematically, and

4. Is subjected to check and control on validity and reliability.

Advantages of the observation method

1. Focuses on the present.

2. Demands less cooperation on the part of the subject.

3. It helps records behavior as it occurs and does not rely on the memory of the respondent or his willingness to part information.

4. It helps capture subconscious habits.

5. It makes possible the study of subjects that are not in a position to respond or are inarticulate e.g. study of recreational behavior of babies, study of animals, etc.

6. Eliminates bias on account of respondent predisposition.

7. It is most suitable for categories of respondents who might misinterpret the objective of the study, e.g. people in rural areas, people living in slums.

8. Mechanical devices can be used.

Limitations of the observation method

1. Expensive and time-consuming method of data collection.

2. It helps record what is happening, but does not give information about why it is happening.

3. Observation poses problems of obtaining a representative sample.

4. Certain behaviour is never accessible and therefore cannot be observed.

5. Certain behaviour is never accessible and therefore cannot be observed.

6. Certain behaviour may not be repetitive or may repeat itself at longer time spans. Such behaviour cannot be observed. The researcher has to wait for the event to occur.

7. The particular setting may affect the behaviour of the subject.

8. The skills of the observer influence to a large extent the quality of data collected.

9. Observation can be of the following types

10. Structured-Unstructured : In the structured observation, the research problem has been formulated precisely and the observe has been given specific instructions about what aspects of behaviour are to be observed and recorded and in what fashion. In unstructured observation the observer is on his own to observe and record whatever he feels is relevant and important.

11. Disguised- Undisguised : Observation in which the subject does not know or is unaware of his being observed by someone is called as disguised observation. Disguised observation helps to observe behaviour in a natural setting, however ethical issues are involved here. Mechanical observation is often disguised. Ghost shopping (posing as a shopper, to observe customer behaviour) is a common form of disguised observation. In undisguised observation the subject is aware of his being observed by the researcher or by some device.

12. Controlled-Uncontrolled : Observation that occurs in a natural settings is called as uncontrolled observation. It helps record behaviour but is affected by extraneous variables. Observation in a laboratory setting is called as controlled observation. It helps control extraneous variable, but the behaviour occurs in an artificial setting.

13. Direct-Indirect : If the event or behavior is observed as it occurs, it is called as direct observation. It some results or records of past behavior are observed, it is called as indirect observation.

14. Human – Mechanical : Observation made by human beings is human behavior. If mechanical or electronic devices (camera, audiometers) are employed the observation is called as mechanical. Mechanical observation is free from subjective bias and fatigue.

15. Experimentation

16. Experimentation is the most sophisticated, exacting and powerful method for discovering and developing an organized body of knowledge. The term experiment implies the pre-existence of certain problem and it involves manipulating certain independent variables with the objective of studying the effect of such manipulation on one or more dependent variables with the objective of studying the effect of such manipulation on one or more dependent variables. Experiments provide a means of answering the question ”what will happen if ..? “. Experiments are generally carried out in a controlled environment. They provide an opportunity to vary the treatment (experimental variable) in a systematic manner, thus allowing for isolation and precise specification of the exact differences.

Advantages of the experimentation method

1. Most effective method for determining causal relationships.

2. It has minimum element of human error.

3. Allows the creation and testing of more conditions than in any other method.

4. Gives reliable, exact and verifiable results.

Limitations of the experimentation method

1. Difficult to establish test and control groups.

2. The scope for experimentation with human beings is limited.

3. It is expensive and time consuming.

4. Requires specialized knowledge

5. Cannot be used for studying the passed events.

It is of little use in studying attitudes, opinions, motives, etc.

Simulation

Simulation is the process of conducting experiments on a prototype or symbolic model representing a phenomenon. It is the exercise of a flexible imitation of processes and outcomes for the

purpose of clarifying or explaining the underlying mechanisms involved. It is a symbolic abstraction, simplification and substitution for some referent system.

Experiments are done on the model instead of the actual system as it would be too time consuming, costly and impractical to experiment on the actual system. Simulation is a technique best suited for study of a system that has a set of interrelated and interdependent sub-systems.

Simulation can be of three types – man simulation, computer simulation, man-computer simulation.

Simulation can be applied to study a range of issues such as – behavioural and social, political, economic, business and trade, war strategies’ and tactics.

Projective Techniques

Projective techniques are data collection tools that help reveal and gather subtle aspects of human behavior and personality. The technique of interviewing assumes that a person is not willing but also capable of reporting aspects of his behavior. Research has, however proved that there are certain aspects of human behavior that cannot be directly figured out and expressed by an individual. Furthermost, an individual may not be willing to discuss controversial and personal issues with the researcher. The projective techniques work on the principle of indirect interviewing, and in the process the respondent reveals his latent, subconscious attitudes, feelings, motives, urges, etc.

Projective techniques involve the presentation of unstructured stimuli to the subject. The stimulus is not selected arbitrarily but is selected in relation to the respondent personality and the object of the test.

The use of projective techniques required specialized traning and careful planning and interpretation. The subject’s responses to the stimuli are not to be taken and face value but must be probed, explored further. The stimuli may arouse a range of responses. There are no right or wrong responses.

Some of the commonly used projective techniques are

1. Word associated tests

2. Sentence completion tests

3. Story completion

4. Verbal projection tests

5. Thematic apperception tests

6. Rosenzweig test

7. Rorschach test

8. Holtzman Inkblot test

9. Doll play test

10. Play techniques

11. Sociometry

12. Quizzes, tests, and examinations.

13. Psychodrama and sociodrama.

Tomkins-Horn picture arrangement test.

Interviewing

It is a two-way purposive communication between the interviewer (researcher) and the respondent (subject) aimed at obtained and recording information pertinent to the subject matter of study. The interviewer presents oral-verbal and written pictorial stimuli and receives oral responses.

It may be used as a supplement to observation, experiments or other techniques. It is versatile in the sense that it can be used to collect a wide range data from demographic profiles, socio-economic classification profiles, to attitudes, beliefs, opinions, values etc. it is also used to study future intensions. It is the only suitable method when qualitative information or probing is necessary.

Interviews help speedy data gathering. It can be also used to gather personal information. The interview technique provides an opportunity to note the body language of the respondent. It also gives room for any clarifications and explanations required by the respondent.

Types of interviews

Structured interviews : deals with standardizes interview or questionnaire research. The questions are pre-determined and the possible answers are also largely pre-determined. More close ended questions are used as compared to the open ended ones. The sequence of questions and the wording is pre-decided.

Advantages of structured interviews.

1. Promotes measurement reliability.

2. Data are comparable across respondents and even across interviews.

3. Recording and coding do not pose problems.

4. Data analysis is easy and can be computerized.

5. The interviewer knows what to ask and what to record.

6. Interviewers can be trained with relatively less effort.

7. The methods places lesser demands on the interviewer’s skills.

8. It is economical.

Limitations of structured interview method

1. Straight jacketing all the respondents minimizes flexibility.

2. It does not have the continuity and spontaneity of natural conversation.

3. The structure of the data collection instrument may minimize the respondent’s views and promote interviewer’s biases.

4. Limited scope of exploration.

5. Not suitable for studies of qualitative nature.

Unstructured interview

Great flexibility in the interview approach and questioning. The techniques and operations are much less standardized. Interviewers do not have to follow a list of questions and categorical responses. If required certain questions can be omitted or supplementary questions may be asked. There is more use of open ended, probing questions, rather than factual, close ended questions.

Advantages of the unstructured interview methods

1. It is useful in a more intensive study of perceptions, attitudes, and motivations.

2. Useful in exploring new avenues of research. Useful in uncovering new hypothesis for further research.

3. It captures social context of beliefs and attitudes – helps to bring out affective and value-laden aspects to determine personal significance.

4. This method permits full and detail expression, unexpected responses.

5. Responses are natural, spontaneous and self revealing rather than forced.

It gives leeway to the interviewer to handle the situation as deemed fit.

Limitations of unstructured interview

1. The procedure is inadequate as a measurement device.

2. Speed of data collection is slow.

3. Flexibility deprives the procedure of its comparability.

4. Interviewers must be sufficiently trained in order to obtain any useful data.

5. Interviewers must display patience, listening skills and empathy.

6. Analysis is difficult and time consuming.

7. Types of unstructured interviews

8. Focused interview : the main function of the interviewer is to focus attention on a given experience and its effects. The interviewer know in advance what topics or what question areas to cover.

9. The interviewer has the freedom to explore reasons and motives and to probe further in direction that he deems fit. Although the participants (respondents) are free to express their thoughts and views, the interviewer is fully in control.

10. Clinical Interview : similar to the focused interview, but differs in the aspect that a clinical interview focuses on the broad underling feelings or motivations or with the course of the individual’s life experiences rather than with the effects of a specific experience. The manner in which questions are asked and their sequence is left largely to the discretion of the interviewer.

Non directive interview : in this type of interview, the initiative is even more in the hands of the respondent. It originated from the field of psychotherapy in which patients are encouraged to express their feelings without directive suggestions or questions from the therapist. The interviewer is supposed to encourage the respondent to talk fully and freely by being alert to the feelings expressed.

Basic methods of interviewing

1. Personal interviews

Telephonic interviews

Advantages of personal interviewing method

1. Better explanations.

2. Depth.

3. Data Quality.

4. Greater Accuracy.

5. Product placement in market research.

6. Flexibility.

7. Greater Control.

8. Handling spontaneous reactions.

9. Adaptability.

10. Supplementary information.

11. Group interviews.

Limitations of personal interviewing method

1. Organization.

2. Control over Interviewers.

3. Cost.

4. Time.

5. Interviewer Bias.

6. Approachability of Respondents.

7. Rapport building.

8. Systematic errors.

9. Inability to articulate.

10. Recording of information.

Advantages of Telephonic interviewing method

1. Low cost per interview.

2. Speedy method of data collection.

3. Short and quick surveys can be conducted.

4. Covers sample spread over wider geographical area.

5. Most suitable method to collect information from higher officials or high net worth individuals.

6. Response rate is quite high.

7. Interviewers are saved the risk of entering dubious neighborhoods.

8. Recalls are easy, call backs are simple and economical.

9. Replies can be recorded accurately.

10. Voice modulation techniques can be employed.

11. Centralized expert interviewing staff can be employed.

12. Computers and other devices can be used effectively.

13. Interviewer bias is reduced.Limitations of telephonic interviewing method

1. Limited to individuals / households with telephonic connections.2. Telephone connections may not be listed in telephone directories.3. Visual aids can not used.4. Respondent gets little time to response.5. Length of interview – 10 to 15 minutes (not suitable for intensive surveys.)6. Telephone directors may yield inadequate samples.7. Questionnaire must contain simple, short, yes-no type questions.8. Information about personal matters is difficult to obtain.9. Interviewer misses out the body language and settings of the responses.

Repetitive probing is not possible.Pre-requisites of successful interviews

1. Training and briefing to the interviewers, followed by mock sessions.2. Making interviewer conversant with data collection instrument and any visual aids used.3. Training about patient listening and proper recording.4. Interviewer is a reporter and not an curiosity seeker or a debater.5. Seeking appointment of respondent.6. Dressing7. Introduction – you and your sponsoring organization.8. Explanation of purpose.9. Creating friendly, secure, reliable and valid atmosphere.10. Do not be too formal or informal.11. Asking question properly and intelligently.12. Skipping and branching instructions.

Pre-requisites of successful interviews continue ….1. Maintaining overall control.2. Training to visual aids.3. Training to ignoring incomplete and non specific answers.4. Record responses accurately and completely.5. Provide evaluative feedback – by using phrases such as “Uh-uuh”, “that’s

interesting”, “thanks for your frank opinion”, “Can you tell me more about that” etc.6. Make habit of inspecting each interview as soon as possible after it is complete.7. Problems associated with interviewing fall into three classes – non response,

inadequate response, and interviewer bias.8. Non-response : Respondent fails in collecting information from some of the sample

elements. Non-response may be on account of non availability, inaccessibility, incapability or refusal. In effect the sample size gets reduced or the sample elements require substitution. The sample size problem can be tackled by a prior estimation of the non-response percentage and increasing the initial sample size accordingly.

9. Inadequate response : there are five principal categories of inadequate response. Viz. partial response, non-response, irrelevant response, inaccurate response and inadequacy due to failure to understand the question or lack of information to answer the question. The remedy to inadequate response is using trained interviewers, through probing, using explanatory phrases wherever deemed essential.

10. Interviewer Bias : there are several ways in which interviewers can influence the responses. The interviewer’s attitudes, his expectations, thinking and influences. Also the respondent’s perceptions of the interviewer’s characteristics (age, sex social status etc.) as well as the interviewer’s perception of the respondent’s characteristics may bias the responses.

The Questionnaire as an Instrument of Data CollectionA questionnaire is a structured sequence of questions designed to draw out facts and opinions and which provides a vehicle for recording the data.Questionnaire serve four purposes

1. To draw accurate information from the respondents.2. Provide structure to the interviews 3. Provides standard form on which facts, comments and attitudes can be recorded.4. Facilitates data processing.

There are mainly three types of interview situation, which in turn need three different types of questionnaires. They are ….

Type of questionnaire

Application Administration of questionnaire

Structured Used for large sample sizes of respondents (above 30), typically when the responses can be closely anticipated.

Personal interviewsTelephonic interviewsMail interviews

Semi-structured

Used where responses cannot be closely anticipated, for small or large sample sizes.

Personal interviewsTelephonic interviews

Unstructured Used for depth interviews, focus groups and areas where probing is essential. Generally limited to small sample sizes.

Group discussionFace-to-Face interviewsDepth interviews

Mail interview : The data collection instrument is administered to a sample of respondents by post.Advantages of mail interviews

1. Lower cost. 2. Possible to cover large geographical areas.

3. Interviewer bias is reduced to a minimum. 4. Less pressure on the respondent for an immediate response. 5. Greater feeling of anonymity to respondent and hence more likely to given open

responses to sensitive questions. Limitations of mail interviews

1. Mail questionnaires can be administered to literate people only and that too having a certain level of education.

2. Lower response rate. Limitations of mail interviews

1. Lowest response rats among the three methods of administering the questionnaire – personal, telephone and mail.

2. Accuracy and completeness may be poor. 3. Only short and simple questionnaires can be administered. Questionnaires with branching

instructions and having numerous statements to be rated are not suitable for mailing. 4. No control over the order in which the questions are responded to. 5. No control over the context in which the questionnaire is answered. 6. No scope for clarifications and explanations, in case of any misunderstandings.

Factors influencing the response rate in postal survey1. Interest of the respondent.2. Availability of accurate database (sampling frame)3. Shorter questionnaire is more likely to be get filled up and mailed back.4. Short, pithy, attractively worded questionnaire printed with covering letter helps in

increasing response rate.5. Second mailing can boost response rate.6. Mailer must not reach the respondent on Mondays, on Fridays and nor on festive

occasions.Mailer must provide a pre-paid response envelope.Questions can be classified as per various bases. Common classifications are ….Open ended – close ended questionsBehavioral – attitudinal classification questionsOpen ended : respondent is free to give any answer and the response is recorded verbatim.Close ended : set of responses is anticipated and are read out or shown to the respondent. These are prompted questions. The answers are worked out through common sense, desk research or a pilot study. Close ended questions are further divided into

1. Dichotomous questions : two options (yes / no, True / False, Male / Female)Multiple choice questionsBehavioral – attitudinal classification questions

Type of question

Information elicited

Behavioral Factual information on respondent profile, ownership patterns, etc. Respondent is the best person to tell more about his present, past and possible future behavior. It records facts and not opinion.Have you ever …. ?

When did you last ….?In the near future will you ….?

Attitudinal Thinking and reasoning, image and rankings, beliefs, values motivations for behavior, etc.Why do you say so?What do your feel about?How do you rate?

Classification Demographic – age, sex, income, socio-economic classification.What is the highest level ….?Which of the following categories …..?

Principles of Questionnaire Design1. Objectives2. Interview method3. Boiler plate information4. Design, printing and layout5. Wording6. Logical order7. Types of questions (open, closed, behavioral, attitudinal, classification etc.)8. Possible answers9. Data processing10. Interviewer instructions

Data Processing & AnalysisOn successful completion of data collection, the next logical step in the research process is data processing and analysis. It includes data reduction and data analysis.To start with, data is edited, followed by data coding, classification and tabulation.Such reduced or edited data is then subjected to various types of statistical analysis.Data processing and data analysis are two different steps.Data processing is concentrating, recasting and dealing with data with the aim of making the collected data amenable to analysis.Data analysis follows data processing and constitutes focusing on the data from the perspective of the hypothesis / research problem.Normally data processing is the part of data analysis. Conceptually these are integrated processes. Analysis of quantitative data is simpler as compared to qualitative data.The broad aspects of data analysis are

• Data Editing • Data Classification • Data Coding • Data Tabulation • Statistical Analysis • Drawing Inferences

Data Editing : very often the interviewer records the responses or his observations, during the course of his administering the questionnaire, in abbreviated form or at times as an illegible scribble. Therefore it is prudent that after each interview is over, he should review the questionnaire to complete abbreviated, shorthand responses, rewrite illegible scribble and correct any omissions.it is the process of examining the data for any obvious errors, omissions, inconsistencies and illegible recording, with the aim of rectifying them at an early stage.It calls for a careful scrutiny of the questionnaires for assessing completeness, accuracy and uniformity.

Editing influences the convenience and speed at later stages of data analysis.Data can be edited at two stages – field editing (same day or next day) and centralized editing (after entire fieldwork – by single qualified editor or team).Inappropriate answers are striked off, answers record in wring units are rectified, no responses are segregated. Data Classification : any research study collects a large volume of raw data. To make any sense out of this huge data, to understand the underlying patterns and for meaningful analysis, it is absolutely essential that the data must be reduced or condensed into a suitable format. The task of arranging the collected data into homogeneous groups or classes based on some common characteristics is called as classification of data.It demands appropriate principle of classification. Classes must be mutually exclusive and collectively exhaustive.The scheme of classification must be linked to the theory and to the objective of the study. The classes established must fulfill the information requirements of the hypothesis testing procedure. Every data item must be classified only once and no data item should be left unclassified.It is better to have more number of classes than fewer classes.Data can be classified accordingly to the presence or absence of an attribute, or the level of an attribute such as awareness, literacy, sex, honesty, confidence etc.Numerical data can be classified into class-intervals.Data Coding : coding refers to the process of assigning numerals or other symbols to the answers or responses. A coding scheme or coding frame needs to be designed for every question, such that the responses fall in specific categories.Care is to be take t define every class along a single dimension or concept. Codification and classification are largely intertwined. It helps the further process of data tabulation.Many times the questionnaire is pre-coded. The respondent himself may be asked to assign appropriate codes to his responses. Coding can be done by the interviewer during the course of interview itself (applicable to dichotomous and multiple-choice questions). In case of open ended questions, usually the coding is done by an experienced coder.Training of the interviewers and coders helps in reducing the inaccuracies. The coders must be explained the rules of coding with appropriate examples. They may be given with dummy data for practice to carry out revisions in the codes.

Data Tabulation : it refers to summarizing the assembled heap of data in the form of matrix in a concise and logical fashion. It reduces data to a compact form. Tabulation builds on the earlier processes of data editing, categorization and coding.Tabulation can be one-dimensional or bidimensional i.e. simple or complex. Simple gives information about one or more groups of independent questions. Complex tabulation gives information about one or more inter-related questions.Give short, clear and relevant title to every table. Give unique number to each table. The source of data be acknowledged on the same page by way of footnote.Use gridlines, comparative data is to be places in adjacent columns or rows, use thick line to differentiate data of different categories, negative figures may have a “minus” sign or may be mentioned in parenthesis. The prime objective of tabulation must be to facilitate the easy fast and accurate processing and analysis.Statistical analysis of Data : it means critical examination of the collected data, reduced to a convenient form so as to study the characteristics of the object under study by the application of statistics.It helps in summarizing the data into a meaningful form, make exact descriptions possible, help to identify the causal factors, aid the drawing reliable inferences, help in arriving at estimates or generalizations, and test various hypotheses at appropriate level of significance.Statistical analysis can be broadly categorized into Descriptive statistical analysis & Inferential statistical analysis.Descriptive Statistical Analysis : gives vivid picture o the subject matter as regards size, composition, preferences, attitudes etc.If the analysis is based on one variable then it called univariate analysis. Two variables then bivariate and multivariate analysis for more than three variables.Multivariate analysis further consists of multiple regression analysis, multiple discriminant analysis, canonical analysis, analysis of variance and factor analysis.Inferential Statistical Analysis : concern with drawing inferences and conclusions from the gathered mass of data. Inferential analysis consists of two areas …. Statistical estimation – involves estimating the population parameters from the sample statistic and is an inherent aspect of any sample survey.Hypothesis testing – it refers to application of statistical techniques to accept or reject the proposed hypothesis at specific levels of significance under assumed population parameters.Types of statistical measuresMeasures of central tendencyMean / average / arithmetic meanMedianModeMeasures of dispersionRangeQuartile deviation or semi-quartile rangeMean absolute deviationStandard deviation

Coefficient of variationRegression analysis

Statistical representationData Set : In Statistics, by a data set, we mean a set or collection of numerical. Example : values as given below ….02, 10, 46, 62, 47, 20, 04, 08, 28, 35,62, 44, 18, 04, 01, 09, 01, 04, 86, 91,00, 129, 116, 03, 21, 02, 48, 106, 100, 09,99, 05, 08, 08, 06, 25, 47, 60, 34, 00,16, 35, 25, 29, 41, 07, 10, 02, 01, 05.Such a set of values is also called raw data. Each value is known as datum and the collection of values data. This is because; they do not have any ‘meaning’ or ‘significance’ on their own, other than their numeric values. Their ‘meaning’ depends on the context to which they are applied.Suppose you are told that this set of values represents the number of runs scored by a batsman in 50 consecutive innings. Then, the data set acquires a meaning and we feel it is meaningful. Arranging Data – Simple ArrayIt is an arrangement of given raw data in ascending or descending order.Numbers 3,5,7,8,9,10 are arranged in ascending order.Numbers 10,9,8,7,6,5,3 are in descending order.Arranging Data – Frequency ArrayA frequency array is a statistical table in which various observations are arranged in order of their magnitude along with their respective frequencies.Number of Children : 0 1 2 3 4 5 TotalNumber of Families : 5 12 14 10 6 3 50

Measures of Central TendencyMeasures of central tendency tell us about the typical score in a distribution. There are three measures of central tendency :Mode – is the number or event that occurs most frequently in a distribution. Median – is the number or score that divides the distribution into equal halves (i.e., the median is the 50th percentile). To be able to calculate the median, you must first rank order the scores.Mean – the mean is defined as the arithmetic average. To find the mean, you add up all the scores in the distribution and then divide by the number of scores that are added.

• Choosing a Measure of Central Tendency :– If you want to know which score occurred most often, then the mode is the

choice.– The median is a better choice to serve as the representative score because it takes

into account all the data in the distribution. However, it treats all scores alike; differences in magnitude are not taken into account.

– When the mean is calculated, the value of each number is taken into account.

• When the scores in your distribution tend to cluster in one of the tails (i.e., a cluster of high or low scores) the distribution is skewed (i.e., a nonsymmetrical distribution). In these instances, the median may be more appropriate.

• The Mean • Four tests results: 15, 18, 22, 20

The sum is: 75Divide 75 by 4: 18.75

• The 'Mean' (Average) is 18.75(Often rounded to 19)

• The Median is the 'middle value' in your list. Thus, remember to line up your values, the middle number is the median! Be sure to remember the odd and even rule.

• Find the Median of : 9, 3, 44, 17, 15 (Odd amount of numbers)Line up your numbers: 3, 9, 15, 17, 44 (smallest to largest)The Median is : 15 (The number in the middle)

• Find the Median of: 8, 3, 44, 17, 12, 6 (Even amount of numbers)Line up your numbers: 3, 6, 8, 12, 17, 44Add the 2 middles numbers and divide by 2: 8 12 = 20 ÷ 2 = 10The Median is 10.

• The mode in a list of numbers refers to the list of numbers that occur most frequently. Most frequently - Mode.

• Find the mode of:9, 3, 3, 44, 17 , 17, 44, 15, 15, 15, 27, 40, 8,Put the numbers is order for ease:3, 3, 8, 9, 15, 15, 15, 17, 17, 27, 40, 44, 44,The Mode is 15 (15 occurs the most at 3 times)

It is important to note that there can be more than one mode and if no number occurs more than once in the set, then there is no mode for that set of numbers.

• The range is simply the smallest number subtracted from the largest number in your set. Thus, if your set is 9, 3, 44, 15, 6 - The range would be 44-3=41. Your range is 41.

• Frequency Distributions – show how often each score occurs in your research. – Some easy steps to follow that will help you construct a frequency distribution

are:• In one column make a list of the categories for which you have

frequencies. If you categories are ordinal, interval, or ratio arrange them in order from highest to lowest.

• Create a second column to the right of the first column. Label this column “tally.” Create a third column to the right of the second. Label this column “frequencies.”

• Convert the tallies to the frequencies and record them in the frequency column.

• Calculate the percentage of occurrence for each category by dividing the frequency for each category by the total number of scores and then multiply by 100. This figure appears in the final column.

Example : Frequency Distributions

Grouped Frequency Distributions

Grouped Frequency Distributions – if you can order your categories numerically from lowest to highest, then you may want to group your frequencies into intervals.

Exclusive Class Intervals

Monthly Income (Rs.) Number of Families

Frequency Distributions – show how often each score occurs in your research.

500 but less than 550 5

550 but less than 600 6

600 but less than 650 10

650 but less than 700 12

700 but less than 750 9

Total 42

Inclusive Class Intervals

Monthly Income (Rs.) Number of Families

500 to 549 5

550 to 599 6

600 to 649 10

650 to 699 12

700 to 749 9

Total 42

Open-end Class Frequency : which has at least one of its ends open.

Class Frequency

Below 25 1

25 - 30 3

30 - 40 5

40 - 50 2

50 and above 1

Total 12

Unequal Class Frequency : classes of a frequency distribution may or may not be of equal width.

Class Frequency

20 - 25 1

25 - 30 3

30 - 40 5

40 - 55 2

55 - 60 1

Total 12

Cumulative Frequency Distribution (“Less-than type”)

Monthly Income (Rs.) Simple Frequencies Cumulative

Less than 550 5 5

Less than 600 6 5+6 11

Less than 650 10 5+6+10 21

Less than 700 12 5+6+10+12 33

Less than 750 9 5+6+10+12+9 42

Cumulative Frequency Distribution (“More-than type”)

Monthly Income (Rs.) Simple Frequencies Cumulative

More than 500 5 9+12+10+6+5 42

More than 550 6 9+12+10+6 38

More than 600 10 9+12+10 31

More than 650 12 9+12 21

More than 700 9

Graphing Your Results

There are several types of graphs from which the researcher can choose. Your choice of graphs will be determined by which one depicts your results most effectively and by the scale of measurement you used.

Pie Chart – depicts the percentage represented by each alternative as a slice of a circular pie; the larger the slice, the greater the percentage.

Bar Graph – presents data in terms of frequencies per category. You can construct a bar graph when you are using nominal (or qualitative) categories that cannot be numerically ordered from lowest to highest

Histogram – represents quantitative data in terms of frequencies

• Frequency Polygon – like the histogram, displays the frequency of each number or score. The only differences between these two graphs are the use of bars in the histogram and the use of connected dots in the frequency polygon.

• Line Graph – in line graphs, there are two axes or dimensions that must be discussed.

• The vertical (Y axis) is known as the ordinate; the horizontal (X axis) is known as the abscissa.

• One of your variables is plotted on the ordinate and the other is plotted on the abscissa.

• A good guideline is to plot the variable that has the greatest number of levels on the abscissa, and thus reducing the number of lines that will appear on your graph.

• A good rule of thumb is for the Y axis to be approximately two thirds as tall as the X axis is long.

Sub-Divided or component Bar Diagram

Multiple Bar Diagram

Year 2009 2010

Total Revenue 30 40

Total Cost 25 35

Profit 5 5

Multiple Bar Diagram

2009 2010 20110

10

20

30

40

50

60

Total RevenueTotal CostProfit

Report writing

The research process is not complete unless the findings of a study are reported. Research becomes useful only when the results are communicated to possible users in a form that is understandable and usable. Research results can be disseminated in many forms, the most common of which are the thesis / dissertation, scientific papers, and articles in research journals.

With a well-written research proposal, half of the research report is almost done. The introduction, literature review and methodology sections of the proposal can be the first three sections of a research report. To these the findings, discussions, conclusions and recommendations sections and references can be added.

What Does Research Report Mean? : A document prepared by a researcher or an analyst or strategist who is a part of the research team. Research reports generally, but not always, have "actionable" recommendations.

Major parts of a research report

Preliminary sections (Title Page – title of the report, author, date, approval sheet, abstract, table of contents, list of tables, figures, acknowledgements)

The Text / Body of the report (Introduction – statement of the problem / research objective, theoretical and conceptual framework, hypothesis, significance of the study, scope and limitations, Literature review, Methodology – design, sampling, data collection technique used, analytical procedures – findings and discussions, conclusions and recommendations.)

FORMAT FOR RESEARCH REPORT

A. Preliminary Section 1. Title Page 2. Acknowledgments (if any) 3. Table of Contents 4. List of Tables (if any) 5. List of Figures (if any) 6. Abstract

B. Main Body 1. Introduction a. Statement of the Problem b. Significance of the Problem (and historical background) c. Purpose d. Statement of Hypothesis e. Assumptions f. Limitations g. Definition of Terms

. Review of Related Literature (and analysis of previous research)

3. Design of the Study

a. Description of Research Design and Procedures Used b. Sources of Data c. Sampling Procedures d. Methods and Instruments of Data Gathering e. Statistical Treatment

4. Analysis of Data

contains:

a. text with appropriate b. tables and c. figures

5. Summary and Conclusions

a. Restatement of the Problem b. Description of Procedures

c. Major Findings (reject or fail to reject Ho) d. Conclusions e. Recommendations for Further Investigation

. Reference Section

1. End Notes (if in that format of citation)

2. Bibliography or Literature Cited

3. Appendix

Preliminary sections

Title page : Contains title of the study, the author and the date of completion. Title must be brief and simply worded.

Abstract : it is a brief descriptive summary of the research report. It includes the statement of the research problem or objectives of the study, a brief description of the research methods used a summary of the major findings, and statement of conclusions and recommendations. Some institutions require an executive summary, which is slightly longer that an abstract.

Approval sheet – the approval sheet provides space for the signatures of the adviser, readers or oral defense panelists, dean and others, indicating their acceptance of the research work.

The table of contents – it is the list of all the parts of the report and the page numbers. The wording, capitalization and punctuations of titles and headings should be written exactly as they are in the text.

List of tables / figures – list with pages numbers. Tables and figures should be numbered consecutively in Arabic numberals throughout the text.

Acknowledgements – writer express appreciation and gratitude for assistance received in the conduct of the study. Acknowledgements must be expressed simply, sincerely and tactfully.

Keywords : In the age of the internet, it is becoming increasingly important to ensure that your research can be found, both on the internet and on university intranet search facilities. Many scientists are moving towards putting a section under the abstract with about 5 – 7 keywords and phrases which will allow search engines to pick up the research work.

The body of the report begins with the first page of chapter 1. Numbering in Arabic numerals starts on this page with Number “1”. All pages in this section are numbered including section or

chapter title pages. Page numbers are positioned one inch from the top of the page at the right margin.

The body of the report is divided into introduction, review of related literature, methodology, findings, discussions and conclusions and recommendations.

Introduction – this provides the background of the research. It explains the need for the study, states the research problem / objectives and hypothesis, if any, specifies the scope and limits of the study, and explains the significance of the problem. All these are found in a well-written proposal. With slight modifications, this section in the proposal can be used in the final report .

The review of related literature, usually written as a separate chapter, should not only summarize the articles, books and other references reviewed, rther call the readers attention to common findings as well as conflicting results of previous studies.

Methodology – describes how the study was conducted. Emphasis should be given to design, sampling procedure, data collection techniques, instruments used, and analytical procedures. The methodology should be discussed in the past tense.

Findings and discussions – the findings of the study constitute the data presentation and the researcher’s analysis of these data. The discussion, which may be written separately from the findings, presents the researchers interpretation of the data, and statements on the implication of the findings to theory and findings of related studies. The discussion goes beyond the data.

Conclusions and recommendations – these are general statements which provide answers to the research problem. Based on the findings and conclusions of the study, recommendations are stated. The implications of the findings for revisioning existing body of knowledge or theories are also be included in this section.

Research Report must have

Analysis and interpretation.

A list of major findings and a list of minor findings.

Thoughtfully written conclusions for the major findings.

Based upon the research experience, particular recommendations for future research with some emphasis on filling gaps.

Findings must be relatively straight-forward.

Conclusions - begin with which hypotheses or expected relationships were supported and which were not. Include statements on the degree to which relationships were significant (generalizable) and the strength of that relationship.

Nearly all scientific papers have a standard format sometimes called IMRAD.

1. I = introduction

2. M= method

3. R= results

4. AD = [and] discussion.

These elements answer questions that the reader is likely to ask:

1. Why did you begin?

2. What did you do?

3. What did you find out?

4. What does it mean?

Title : The title should be indicative and should clearly indicate topic and scope. Avoid abbreviations and initialisms. The title should be brief and use the fewest possible words that adequately describe paper content. Insure that each word is needed. Avoid word wasters such as "studies on, investigations on, analysis of, characteristics of" and the like. Use specific rather than general terms. The title of a paper is a label and not a sentence.

Authors : Only those who made a major contribution to the completed product should be included. Co-authors may add considerable strength, substance, and a fresh perspective. Others who were helpful should receive credit in the acknowledgements section.

The order of the authors should be agreed before the research. The first author receives more credit than the second one. Ways of ordering may include:

• Alphabetical

• Seniority

• Proportional to their contribution [may be difficult].

Institutional affiliation adds creditability and some status to authors [depending upon the institution]. This may have a role in co-authors and author ordering.

Introduction : The introduction begins with the problem statement. The problem should be clearly identified in nature and scope in the first paragraph. Why it is a problem and why the problem is important should also receive attention.

There should be enough background to convince the reader that the topic is well worth exploring, to set the stage, but no more than that. A common error among beginning researchers is to bog down in this section of the research report.

Following the problem statement and context, the researcher sets forth the purpose of the research and what will be done. Be careful because this may serve as a yardstick for those who measure the success of the research project.

The introduction ought to be informative enough so that the reader can understand and evaluate your work without needed to refer to anything else.

Material & Method : Ideally, the interested reader ought to be able to replicate your study from the information found in this section. Be precise and include enough details to do this or indicate early in this section that this information is available from the author.

Normally, you would present your hypotheses in this section since they will guide the method.

This sections answers three fundamental questions:

1. What did you do?

2. Why did you do it?

3. How did you do it?

Select a level of detail appropriate for your audience. If in doubt, review the methods section of similar papers published in the target periodical [the one where you hope to be published]. Ordinary statistical methods or test should be used without comment or explanation.

Results : This is the most important section of the paper. The evidence provided here is what the reader is most interested in. It describes findings. The section is data oriented and does NOT include interpretation.

Here all findings are reviewed and put into two sections : major findings and minor findings. Major findings are essential and useful and hence required to be focused. If there are a reasonable number of interesting but minor findings, provide a foot or end note saying that information on these is available from the author.

Tables, charts, and graphs are better for presenting findings than text. Do not construct tables unless there is a reasonable amount of data to be presented. Use no more digits than are necessary. Be consistent in how you present the data and the labels that you use. Say it only once in text or in table or in graph. You may use text to briefly summarize a somewhat complex chart, table, or graph, but you do not present the same information in various formats.

If there is any sort of a trend or an interesting "picture," use a graph. If the numbers just sit there, use a table. Charts and graphs make the report more interesting and grab the reader's attention. However, they must be well-designed, informative, and reproduce well.

Discussion or Conclusions : This section would also include suggestions for further research. Some to many readers will skip the results section and begin thoughtful reading here. Discuss the results, but do not repeat them in any detail. The point is to add interpretation or "so what" to the major findings in the previous section.

Although not always done, you may briefly comment on deficiencies in this report and relate those to suggestions for further research.

There is a natural order:

1. State and support/reject your hypotheses

2. Outline previous published results that relate to the hypotheses and comment on the degree to which your results match theirs

3. Identify snags or problems encountered [how I would do it better next time]

4. Draw conclusions on the basis of the evidence

5. Make recommendations for further research that are well linked to this research.

Acknowledgements

Briefly identify those who were helpful, including local institutional help and funding agencies.

References or Citations or Notes

Publishers have very specific standards for these so follow their instructions to the authors exactly.

Never cite a reference unless you have read the original.

Only cite items that were both important and useful.

Appendices

Here place supporting material that is not critical to understanding the text, but that will interest some readers. Instruments such as an interview schedule or a questionnaire are good examples. This improves the flow and readability of the main text.

The Abstract

This is written at the end because only then you know exactly what you did and exactly what you found.

Normally, do not exceed 125 words for shorter papers and 250 words for longer papers. Another perspective is that the abstract should not be greater than five percent of the article length.

This is formatted as one paragraph. It is limited to intellectual content that appears in the paper. There should be no unidentified abbreviations, initialisms, or references.

Abstracts come in two flavors

Descriptive : Also sometimes called "indicative" and are a kind of table of contents presented in a narrative style.

Informative : These summarize the main problem, method, findings, and conclusions. This is the most common model. You want to help the reader to make a relevance decision, but you don't want them to substitute reading the abstract for reading the whole article.

Use of Computers in Research

Compilation of vast amounts of data.

Complex data analysis

Solving mathematical equations : Scientific research often requires that complex mathematical equations be solved in order to determine if data is valid or if a certain structure will remain stable. Computers are integral to this calculation process since scientists can write software programs specifically to provide answers to such questions. This removes the element of human error, which can cost research institutions millions of dollars in fixing a product that was created with even the smallest amount of flawed data.

Prediction modeling : Scientists and researchers are able to use computer programs to model how data might manifest itself in the future.

Creates research results with fewer errors and better-engineered products.