By Jairaj Gupta

managerial statistics:an overview

By Jairaj Gupta

“ there are three kinds of lies: lies, damned lies and statistics.”……

Benjamin Disraeli

By Jairaj Gupta

Statistics:

Statistics is a art and science pertaining to the collection, analysis, interpretation or explanation, and presentation of data.

By Jairaj Gupta

Utility of statistics:

To understand the reason for variation of a data and its causes to take better decision about a phenomenon that produced it.

By Jairaj Gupta

Characteristics of statistics:

It deals with aggregate of facts.These are affected to a marked extent by

multiplicity of causes.These are numerically expressed.These are enumerated or estimated according to

reasonable standard of accuracy.These are collected in a systematic manner.These are collected for a pre-determined purpose.These are placed in relation to each other.

By Jairaj Gupta

Statistics in business management:

Marketing

Production

Finance

Personnel

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Concept of sample and population:

Population is the total group of respondents that the researcher wants to study. Populations are too costly and time consuming to study in entirety. Sample is a section of the population that we are actually going to survey. It is important to have a sample that will represent our entire population in order to minimize biases.

E.g.: You want to know how American citizens feel about the war in Iraq. Your population: The United States. Your sample: 500 citizens selected randomly from each state.

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Concept of statistics & parameter:

Characteristic of a sample is called statistics and characteristic of a population, which is inferred on the basis of the sample statistics is called parameter.

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Types of statistical methods:

Descriptive

Descriptive statistics includes statistical method involving the collection, presentation & characterization of a set of data in order to describe it’s various features. They provide simple summaries about the sample and the measures. Together with simple graphics analysis, they form the basis of virtually every quantitative analysis of data.

Inferential

With inferential statistics, we are trying to reach conclusions that extend beyond the immediate data alone. For instance, we use inferential statistics to try to infer from the sample data what the population parameter might be.

By Jairaj Gupta

Limitations of statistics:

It does not study qualitative phenomenon.

It does not study individual fact or observation.

It can be misused.

Statistical results are true only on an average.

By Jairaj Gupta

Data:

Data are collection of any number of related observations.

A collection of data is called a data set, and a single observation data point.

By Jairaj Gupta

Qualitative & quantitative data:

Qualitative

Deals with descriptions.

Data can be observed but not measured.

E.g. color, texture, smell, beauty etc.

Quantitative

Deals with numbers. Data which can be

measured. E.g. length, height,

area, volume, speed etc.

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Concept on discrete & continuous data:

A type of data is discrete if there are only a finite number of values possible or if there is a space on the number line between each 2 possible values.

Ex. A 5 question quiz is given in a Math class. The number of correct answers on a student's quiz is an example of discrete data. The number of correct answers would have to be one of the following : 0, 1, 2, 3, 4, or 5.

Continuous data can take up any numerical value. This is a type of data that is usually associated with some sort of physical measurement.

Ex. The height of trees at a nursery is an example of continuous data. Is it possible for a tree to be 76.2" tall? Sure. How about 76.29"? Yes. How about 76.2914563782"? Yes.

By Jairaj Gupta

Sources of data:

Primary source: source that itself collects the data.

Secondary data: source that uses available data which were collected by some other agency.

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Primary Data:

Data never gathered before or first hand data.

Advantage: find data you need to suit your purpose

Disadvantage: usually more costly and time consuming than collecting secondary data

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Types of Primary Data: Demographic/Socioeconomic

Age, Sex, Income, Marital Status, Occupation Psychological/Lifestyle

Activities, Interests, Personality Traits Attitudes/Opinions

Preferences, Views, Feelings, Inclinations Awareness/Knowledge

Facts about product, features, price, uses Intentions

Planned or Anticipated Behavior Motivations

Why People Buy (Needs, Wants, Wishes, Ideal-Self) Behavior

Purchase, Use, Timing, Traffic Flow

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Methods of collecting primary data:

Direct personal interviewIndirect oral interviewsInformation from correspondentsMailed questionnaire methodSchedules sent through enumerators

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Direct personal interview: There is face to face contact of the surveyor with the respondent.Merits: Respondent feels encouraged to answer. Information obtained is more correct as the interviewer can clear up

the doubts pertaining to certain questions & can even cross-examine. Sensitive questions can be cleverly dealt after analyzing the

psychology of the respondent. Language of communication could be adjusted if required.Demerits: Costly Chances of personal prejudice & bias is higher compared to other

methods. Interviewer needs to be an expert in his area Time consumingSuitability: where intensive study of a limited field is desired

By Jairaj Gupta

Indirect oral interview:

Here the interviewer contacts third party capable of supplying necessary information. It is generally adopted in those cases where the information to be obtained is of complex nature and the informants are reluctant to respond if approached directly. E.g. information regarding addiction to drug, alcohol, visiting prostitutes etc.

By Jairaj Gupta

Information from correspondent:

Here the investigator appoints local agents or correspondents in different place to collect information. Newspaper agencies generally adopt this method. However the information may be affected by the personal prejudice and bias of the correspondent.

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Mail questionnaire method: Here a list of questions pertaining to the survey is prepared and sent

to the various informants by post.Merits: Most suitable when field of investigation is vast and informants are

spread over wide geographical area. Relatively cost effective. Respondents can fill it in her own preferred time & may consult others

if required.Demerits: Respondent needs to be literate, can’t be used for illiterates. Involves uncertainty about response. Information may be wrong & may be difficult to verify the accuracy.

By Jairaj Gupta

Schedules sent through enumerators:

Schedules (is the name usually applied to a set of questions which are asked and filled in a face-to-face situation with another person) are sent through interviewers or enumerators to get replies of the questions in the schedule from the respondents.

Merit: Illiterate can participate as questionnaire is filled by enumerators. Rate of response is high as respondents are contacted personally.Demerits: Involves high cost Time consuming Training and expertise of enumerator is required

By Jairaj Gupta

Secondary data:

Secondary data is data collected by someone other than the user. Common sources of secondary data for social science include censuses, surveys, and organizational records.

By Jairaj Gupta

Advantages and Disadvantages of secondary data:Advantages:

Resource implications – usually easier to gather than primary data Cost & time effective Deficiencies & gaps can be identified easily and rectification

measures could be take to overcome them. Quality and permanence of data – eg. government surveys

Disadvantages:

Suitability Cost and access – may still be difficult in spite of resource

advantages Validity of some secondary data (eg. Internet sources)

By Jairaj Gupta

Constructing the Questionnaire:Select the correct types of questions:open ended – harder to score but get

“richer” informationclosed ended, dichotomous – offer

two either/or responses (true/false; yes/no; for/against

multiple choice – select one or more than one

scaled response – gather range of “values” (strongly disagree, somewhat disagree, neutral, somewhat agree, strongly agree

By Jairaj Gupta

Important characteristics of good questionnaires:

Plan a user-friendly format.Gather demographic data – age, gender, etc., when

necessary. Guarantee anonymity (without name).Ensure ease of tabulation.Ask well-phrased and unambiguous questions that

can be answered.Develop for completeness – get all the data.Pilot test the instrument.

By Jairaj Gupta

Sample Questionnaire:

By Jairaj Gupta

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