Measurement and Scaling - Research Methodology

1. MEASUREMENT AND SCALING  
2. MEASUREMENT  - Measurement is defined as process of associating numbers or symbols to observations obtained in a research study
3.  These observation could be qualitative or quantitative. 
4.  It is difficult to measure abstract or qualitative characteristics than quantitative characteristics 
5. It is easy to measure properties like weight ,height etc. by some standard unit of measurement
   
6. But it is difficult to measure properties like motivation , honesty, customer’s perceptions, brand loyalty etc. 
7. Example: We can record a person’s marital status as 1 ,2 , 3 or 4 depending on whether the person is single, married , widowed or divorced. We cannot make comparison between these numbers but can be count each number
8. Classification of measurement scales
9.  a) Nominal Scale
10.  b) Ordinal Scale
11.  c) Interval Scale 
12. d) Ratio Scale 
13. The most widely used classification of measurement are :
14. Nominal Scale -  Nominal scale is the most elementary form of measurement . 
15.  It is simply a system of assigning number symbols to elements in order to label them. 
16.  For example , a population may be classified as males and females. Males can be assigned numeral as 1 and females as 2 . 
17. Members of a labeled set can only be counted.  
18. Mode is the only measure of central tendency that can be applied. Chi – squire test is the most common test of statistical significance
    
19. Ordinal Scale -Ordinal scale places elements in order. It ranks objects or elements from one largest to smallest or first to last. 
20.  For example: ranking of students according to scores obtained by them. 
21. Ordinal scale represent which is greater and which is lesser. 
22.  Appropriate measure of central tendency is median.  Percentile is used for measuring dispersion
23. Interval Scale - It assumes that the measurements are made in equal units. i.e. gaps between whole numbers on the scale are equal.  e.g. Fahrenheit and Celsius temperature scales
24.  An interval scale does not have a true zero. e.g. A temperature of "zero" does not mean that there is no temperature...it is just an arbitrary zero point. Permissible statistics: count/frequencies, mode, median, mean, standard deviation
25. Ratio scale represnts the actual amount of variables. Eg; measures of physical dimensions such as height, weight ,distance etc. similar to interval scales except that the ratio scale has a true zero value. e.g. the zero point on a centimetre scale indicates the complete absence of length or height, allows to compare differences between numbers.Permits full arithmetic operation.
26.  Examples height, weight, age, Length time Income Market share 1.What is your annual income before taxes? Rs;_______ 2. How far is your workplace from home? _______ miles
27. Scale Basic Characteristics-  Common Examples Marketing ,Nominal Numbers identify & classify objects Social Security nos., numbering of football players Brand nos., store types Percentages, mode Chi-square, binomial test Ordinal Nos. indicate the relative positions of objects but not the magnitude of differences between them Quality rankings, rankings of teams in a tournament Preference rankings, market position, social class Percentile, median Rank-order correlation, Friedman ANOVA Ratio Zero point is fixed, ratios of scale values can be compared Length, weight Age, sales, income, costs Geometric mean, harmonic mean Coefficient of variation Permissible Statistics Descriptive Inferential Interval Differences between objects Temperature (Fahrenheit) Attitudes, opinions, index Range, mean, standard Product- moment
28. Classification of Scaling Techniques
29. Comparative scales; Involve the respondent directly comparing stimulus objects. • e.g. How does Pepsi compare with Coke on sweetness Noncomparative scales; Respondent scales each stimulus object independently of other objects • e.g. How would you rate the sweetness of Pepsi on a scale of 1 to 10
30. Paired Comparison Scaling - A respondent is presented with two objects and asked to select one according to some criterion. The data obtained are ordinal in nature.Paired comparison scaling is the most widely-used comparative scaling technique. It is given by the formula, N=[n(n - 1) /2] , 
31. where `N’ – number of judgements
32.  ` n’ – Number of stimuli or objects to be judged. 
33. Under the assumption of transitivity, it is possible to convert paired comparison data to a rank order 
34. Respondents are presented with several objects simultaneously and asked to order or rank them according to their choices.
35.  It is possible that the respondent may dislike the brand ranked 1 in an absolute sense.
36. Furthermore, rank order scaling also results in ordinal data.  It is easier and faster than the method of paired comparison
37.  It is used to assess the relative importance attached by a respondent to the stimulus objects.  The respondents gives certain points to each stimulus objects out of a fixed sum of points. The fixed sum is usually taken as 100, but it could be other value also.
38. Continues rating or graphic rating Respondents rate the objects by placing a mark at the appropriate position on a line that runs from one extreme of the criterion variable to the other.
39.  Itemized Rating Scales - The respondents are provided with a scale that has a number or brief description associated with each category.
40. The categories are ordered in terms of scale position, and the respondents are required to select the specified category that best describes the object being rated.The commonly used itemized rating scales are the Likert, semantic differential, and Stapel scales.
41. The Likert Scale The Likert scale requires the respondents to indicate a degree of agreement or disagreement with each of a series of statements about the stimulus objects.
42. The analysis can be conducted on an item-by-item basis (profile analysis), or a total (summated) score can be calculated.
43. When arriving at a total score, the categories assigned to the negative statements by the respondents should be scored by reversing the scale. Response alternatives: “strongly agree”, “agree”, “uncertain”, “disagree”, and “strongly disagree”.
44. Generally use either a 5- or 7-point scale
45. Semantic Differential Scales - The semantic differential is a seven-point rating scale with end points associated with bipolar labels that have semantic meaning. 
46. The negative adjective or phrase sometimes appears at the left side of the scale and sometimes at the right. 
47. This controls the tendency of some respondents, particularly those with very positive or very negative attitudes, to mark the right- or left- hand sides without reading the labels.
48. Individual items on a semantic differential scale may be scored on either a -3 to +3 or a 1 to 7 scale.
49. The Stapel scale is a unipolar rating scale with ten categories numbered from -5 to +5, without a neutral point (zero). This scale is usually presented vertically. The data obtained by using a Stapel scale can be analyzed in the same way as semantic differential data.
50. Scale Basic Characteristics
51. Examples Advantages 
52.  Continuous Rating Scale 
53. Place a mark on a continuous line
54. Reaction to TV commercials
55.  Easy to construct Scoring can be cumbersome unless computerized Itemized Rating Scales Likert Scale Degrees of agreement on a 1 (strongly disagree) to 5 (strongly agree) scale Measurement of attitudes Easy to construct, administer, and understand
56. Disadvantages
    
57.  More time-consuming 
58. Semantic Differential Seven- point scale with bipolar labels Brand, product, and company images
59.  Versatile Controversy as to whether the data are interval
60.  Stapel Scale Unipolar ten-point scale,- 5 to +5, without a neutral point (zero) Measurement of attitudes and images Easy to construct, administer over telephone Confusing and difficult to apply Basic Noncomparative Scales.