1. While using relevant examples, discuss all the measurement scales used in research (15 Marks).2. Explain all the procedures of doing a good questionnaire (15 Marks)

Discuss: Essentially this is a written debate where you are using your skill at reasoning, backed up by carefully selected evidence to make a case for and against an argument, or point out the advantages and disadvantages of a given context. Remember to arrive at a conclusion.

Solutions

1. Scale of measurement refers to how variables are measured. There are five different scales of measurement:

Measurement Scales

The type of data collected determines the appropriate measurement scale, and the measurement scale, in turn, determines the appropriate statistical procedure for analyzing particular data and drawing conclusions from that data. Each type of measurement scale has a specific use. Nominal scales. Nominal scales are composed of sets of categories in which objects are classified. For example, a nominal scale dealing with household pets might include the categories dogs, cats, birds, and fish. Data used in the construction of a nominal scale are frequency data, the number of subjects in each category (in this case, the number of animals for each type of pet).

The nominal scale forms the basis for such analyses as Analysis of Variance (ANOVA) because those analyses require that some category is compared to at least one other category. The nominal scale is the lowest form of measurement because it doesn’t capture information about the focal object other than whether the object belongs or doesn’t belong to a category

Ordinal scales.

Ordinal scales indicate the order of the data according to some criterion. For example, a researcher might ask people to rank their preference for types of household pets, with 1 as the most preferred and 4 as the least preferred (resulting in, perhaps, 1 dogs, 2 cats, 3 birds, 4 fish). Ordinal scales tell ‐ ‐ ‐ ‐nothing about the distance between units of the scale (for example, although dogs may be preferred to cats, no information is available about the extent of that preference) and supply information only about order of preference.

The ordinal scale has at least one major advantage over the nominal scale. The ordinal scale contains all of the information captured in the nominal scale but it also ranks data from lowest to highest. Rather than simply categorize data by placing an object either into or not into a category, ordinal data give you some idea of where data lie in relation to each other.

Interval scales.

Interval scales have equal distances between scale units and permit statements to be made about those units as compared to other units (that is, one unit may be a certain number of units higher or

lower than another), but they do not allow conclusions that one unit is a particular multiple of another because on interval scales there is no zero. That is, the scale does not allow for the complete absence of the phenomenon being measured. For example, if you refer to the interval scale used on a thermometer, you can say that 88 degrees is 2 degrees higher than 86 degrees, but you cannot accurately say that 88 degrees is twice as hot as 44 degrees because there is never a situation of no heat at all. (The zero on a thermometer doesn't indicate a complete lack of heat, only one more unit on the scale, which continues downward.) Interval scales, then, permit a statement of “more than” or “less than” but not of “how many times more.”

Ratio scales.

Ratio scales have equal distances between scale units as well as an absolute zero. If you're measuring the height of two trees and tree A is 36 inches tall and tree B is 72 inches tall, you can accurately say that B is twice as tall as A. There is a condition of zero height. Most measures encountered in daily living are based on a ratio scale.

Continuous and discontinuous scales.

Measures may also be categorized according to continuity and discontinuity. A continuous scale is one in which the variable under consideration can assume an infinite number of values. A person's height, for example, might be expressed in an infinite number of ways, ranging from feet, to inches, to tenths of inches, to hundredths of inches, and so forth according to how small or large a measurement one wants to make. On the other hand, discontinuous, or discrete, scales express the measurement of the variable under consideration in a finite number of ways, as, for example, in a frequency distribution such as the number of students in a psychology department or the number of players on a team.

Conclusion

The four levels of measurement discussed above have an important impact on how you collect data and how you analyze them later. Collect at the wrong level, and you will end of having to adjust your research, your design, and your analyses. Make sure you consider carefully the level at which you collect your data, especially in light of what statistical procedures you intend to use once you have the data in hand.

2. Process of making a Questionnaire

2. 1) Defining the objectives of the surveyThis part makes the writer of the questionnaire is to identify the points that might dissatisfy the person taking the questionnaire.

They’ve also got to make the questionnaire get to the point of what you are trying to get to. For example, you will have to put questions in it that have some sort of value to what you are doing.

2.2) Determining the sampling groupThis is an important part of the process as without a proper sample group the answers that you get back from the questionnaire wont be very valid and therefore it wont bring back good results.Also, you have to base the questionnaire at a specific sample group as it could be difficult giving the same questionnaire out to everyone and then trying to get them to give it back.

2.3) Writing the questionnaireAt this point we should know what we want to measure and therefore writing the questionnaire should be easy (or at least easier than the beginning!) to write.It also important to only ask the background questions that are necessary as you won’t have their attention for very long and a questionnaire is supposed to be short.

At this point the survey should be designed according to how it will be administered ie. By computer, mail, phone, on paper or live person.

2. 4) Administering the questionnaireThis part is getting the questionnaire checked and made sure that it is right for when it gets ‘released’, it is done by testing it on friends, employees or family . This has to be done because if it is not correct it could make the interviewee feel like they are stupid and therefore the questionnaire won’t be good.Also, interviewee’s have the desire to please therefore answers could be invalid.

2.5) Interpretation of the resultsThis is the ending of the questionnaire and where the results come in to be analyzed.How we interpret the results is an important part of the process as this can help us with what we want to produce (depending on what you want the results for).Also, it could help us with making our target market a lot more specified and therefore the product will be a lot better.

Alternate (Designing a good questionnaire)

1. Definition of objectives

the writer identifies the points that might dissatisfy the person taking the questionaire. The questionaire must also be focused onto the research problem.

2. Determining the sampling group

Without a proper sampling group the questionaire feedback wont be valid and therefore brings poor results. The questionaire should be based on a particular sample group as it would be difficult to give the same questionaire to everyone and trying to get them give it back.

3. Writing the questionaire

At this point we should know what we want to measure and therefore writing it would be easy. Necessary background questions should be asked to capture the attention of the respondent and as their attention span is small, the questionaire should be short.

4. Administering the questionaire

In this part the questionaire gets checked to make sure that it is right for when it is released. This has to be done because if it is not correct it could make the interviewee feel like they are stupid and therefore the questionaire wont be good.

5. Interpretation of the results

This is the ending of the questionaire and where the results come in to be analysed. How the results are interpereted is very impartant part of the process as it can help with what we want to produce. It could also help with making our target market much more specified and therefore the result will be much more better.