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Research Methodology Chapter 8 & 9. Measurement of Variables Business research deal with various social, psychological and behavioral variables. Their.

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Presentation on theme: "Research Methodology Chapter 8 & 9. Measurement of Variables Business research deal with various social, psychological and behavioral variables. Their."— Presentation transcript:

1 Research Methodology Chapter 8 & 9

2 Measurement of Variables Business research deal with various social, psychological and behavioral variables. Their measurement is one of the vital stage in the research process. It is a complex and demanding task. Unless the variables are measured in some way, a researcher will not be able to test the framed hypotheses and find answer to complex research issues.

3 Definition It can be defined as the assignment of numerals to objects or events according to rules. It is nothing but assigning numbers to represent properties of a concept. For example: Applicants can be classified on the basis of their sex. The rule is assign 0 if female and assign 1 if male.

4 What is measured ? Objects that can be physically measured by some instruments do not pose any measurement problems. Example: Length and width of an office table, demographic characteristics, objective performance of the labour, etc. However, measurement of peoples subjective feelings such as, attitudes, perceptions, behavior and etc become difficult. This need special attention in business research.

5 Types of Variables and Measurement Problem Broadly the variables can be divided into two types: Objective Variables: Possible for clear and accurate measurement Subjective Variables: Not possible for clear and accurate measure. These kind of variables should be measured indirectly.

6 Measurement of Subjective Variables Despite the lack of objective measuring device to measure the subjective variables, there are ways of tapping the subjective feelings and perceptions of individuals. One technique is to reduce the abstract concepts into observable behavior and characteristics. This is called as operationalizing the concepts.

7 Operational Definition of a Concept Operationally defining a concept is done by looking at the behavioral dimensions or properties denoted by the concept. These are then translated into observable and measurable elements so as to form an index of measurement of the concept.

8 Dimensions (Characteristics) It is a specifiable aspect of a concept. For example, understanding, recall and application are some of the specifiable aspects of the concept of learning. A concept can be subdivided into several clearly defined dimensions.

9 Elements (indicator) Definite meaning to a concept will specify one or more indictors what we have in mind. An indicator is a sign of the presence or absence of the concept we are studying with the unit of analysis. An indicator is called as a element. These elements are grouped into different specifiable aspects of a concept. A specifiable aspect is called as a dimension of the concept.

10 Elements: Example Indicator of the Concept Learning: Answering questions correctly Give appropriate examples (These two indicators can be grouped as a dimension called understanding aspect of learning) Solve practical problem Integrate with other relevant material ( These two indicators can be grouped as dimension called application aspect of learning)

11 LEARNING UnderstandingApplication DD Answering questions correctly Give appropriate examples Solve practical problem Integrate with other relevant material EEEE

12 Measurement We have learned how to operationalize concepts, and now we need to measure them in some manner. In chapter 8 (textbook) we will examine the types of scales that can be applied to measure different variables. Whereas in chapter 9, we will see how we apply them (scaling techniques).

13 Scales A scale is a tool or mechanism by which individuals are distinguished as to how they differ from one another on the variables of interest to our study. Scales are efficient data reduction devices. They allow us to summarize several indicators in a single numerical score. Hence it is called as composite measure.

14 Nominal Measurement This is the simplest and lowest level of measurement. It is useful for categorizing variables into sub-classes by assigning a numerals of any other symbols to mutually exclusive sub-classes. For example the variable of sex is classified as males 1 and females 2 or as M and F. Nominally scaled numbers only act as a labels for the classification. Therefore, we cannot perform any arithmetic operations on these numbers because they only indicate the presence or absence of some characteristics.

15 Ordinal Measurement In this level of measurement, objects or persons are order by rank. Ranks are assigned in ascending or descending orders. This level of information contains all the information of a nominal scale plus some relative means of ordering. Moreover, this measurement is useful to perform some statistical analysis, like, rank correlation, median, and non-parametric tests.

16 Interval Measurement This measurement has the powers of nominal and ordinal measurements plus one additional strength – the concept of equality of interval. But the numbers on an interval scale cannot be multiplies or divided, since the scale does not have any true zero. Thermometer is a typical example for interval level of measurement. More powerful statistical techniques can be used with interval scales are, measures of central tendency, dispersion, correlation and some test of significance.

17 Ratio Measurement This is the highest and most ideal level of measurement. This is suitable for measuring properties which have natural zero points. Since there is an absolute natural zero, all arithmetic operations including multiplication and division are possible. Examples are weight, height, distance, money value, population counts, rate of return and so on. This measurement is suitable for all statistical and mathematical treatments.

18 Techniques/Methods of Scaling There are 4 types of scales that can be used to measure the operationally defined dimensions & elements of a variable. It is also necessary to examine the methods of scaling (that is, assigning numbers or symbols) to elicit the attitudinal responses of subjects toward objects, events, or persons.

19 Scaling Techniques Frequently Used Popularly used scales can be classified into two categories namely: rating and ranking scales. Rating Scale: In a rating scale, the rater evaluates a single dimension of a person, object or other phenomenon at a particular point. Attitude scales measure an individuals attitude toward any object or phenomenon. Attitude scales are combinations of rating scales. Ranking Scale: Ranking scales, on the other hand, make comparisons between or among objects, events, or persons and elicit the preferred choices and ranking among them.

20 Rating Scales Dichotomous scale Category scale Likert scale Semantic differential scale Numerical scale Fixed or constant sum rating scale Itemized rating scale Graphic Scale Consensus Scale

21 Dichotomous Scale The dichotomous scale is used to elicit a yes or no answer, as in the example below. Do you own a car? Yes = 1 No = 0 This is an example for the nominal scale.

22 Category Scale The category scale uses multiple items to elicit a single response as per the following example: What is your race? Malay Chinese Indian Others This is also a nominal scale

23 Likert Scale The Likert scale is designed to examine how strongly subject agree or disagree with statement on a 5-point scale: Strongly Disagree = 1 Disagree= 2 Neither Agree nor Disagree= 3 Agree= 4 Strong Agree= 5

24 Semantic Differential Scale Several bipolar attributes are identified at the extremes of the scale, and respondents are asked to indicate their attitudes. Example: Responsive Unresponsive This is treated as an interval scale.

25 Numerical Scale It is similar to the semantic differential scale with the difference that numbers on a 5 – point or 7 point scale. It is also a interval scale Example: How pleased are you with your new real estate agent? Extremely Pleased Extremely Displeased

26 Fixed or Constant Sum Scale Here the respondents are asked to distribute a given number of points across various items as per the example below. This is more in the nature of an ordinal scale. Example: In choosing a toilet soap, indicate the importance you attach to each of the following five aspects by distributing a total of 100 points among them. Fragrance, Color, Shape, Size and Texture of lather.

27 Ranking Scales Paired Comparison Forced Choice Comparative Scale

28 Paired Comparison The respondents are asked to choose between two objects at a time. This helps to assess the respondents preferences. For example: Respondents may be asked to select more desirable occupation from each of the pairs, out of the five occupation considered. The paired choice of n objects will be [n (n-1)/2].

29 Forced Choice The forced choice offers respondents the opportunity to rank objects relative to one another, among the alternatives provided. Example: Rank your preferences among the following magazines, which you would like to subscribe to, 1 being the most preferred choice and 4 being the least preferred. Fortune, Playboy, Time and People

30 Goodness of Measures The use of better instruments will ensure more accurate results, which in turn will enhance the scientific quality of the research. Hence, in some way we need to assess the goodness of the measures developed, that is reliability and validity.

31 Reliability and Validity Reliability: Reliability tests how consistently a measuring instrument measures whatever concept it is measuring. In other words, reliability is concerned with stability and consistency in measurement. Validity: Validity tests how well an instrument that is developed measures the particular concept it is supposed to measure. In other words, it is concerned with whether we measure the right concept.

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