Chapter Eight Measurement and Scaling Fundamentals Copyright 2010

Chapter Eight Measurement and Scaling Fundamentals Copyright © 2010 Pearson Education, Inc. 8 -1

Chapter Outline 1) Measurement and Scaling 2) Primary Scales of Measurement i. Nominal Scale ii. Ordinal Scale iii. Interval Scale iv. Ratio Scale Copyright © 2010 Pearson Education, Inc. 8 -2

1 - Measurement and Scaling Measurement means assigning numbers or other symbols to characteristics of objects according to certain pre-specified rules. Scaling involves creating a continuum upon which measured objects are located. Example: consider a scale from 1 to 10 for located consumers according the characteristic “attitude toward department stores”. Each respondent is assigned a number from 1 to 10 indicating the degree of favorableness or un-favorableness, with 1= extremely unfavorable and 10= extremely favorable. Measurement is the actual assignment of a number from 1 to 10 to each respondent. Scaling is the process of placing the respondents on a continuum with respect to their attitude toward department stores. Copyright © 2010 Pearson Education, Inc. 8 -3

2 - Primary Scales of Measurement Nominal Numbers Assigned to Runners Finish 7 Ordinal Interval Ratio 8 3 Rank Order of Winners Performance Rating on a 0 to 10 Scale Time to Finish in Seconds Copyright © 2010 Pearson Education, Inc. Finish Third place Second place First place 8. 2 9. 1 9. 6 15. 2 14. 1 13. 4 8 -4

Illustration of Scales of Measurement Nominal Scale Ordinal Scale Interval Scale Ratio Scale No. Store Preference Rankings Preference Ratings 1 -7 $ spent last 3 months 1. Parisian 2. Macy’s 3. Kmart 4. Kohl’s 5. J. C. Penney 6. Neiman Marcus 7. Marshalls 8. Saks Fifth Avenue 9. Sears 10. Wal-Mart Copyright © 2010 Pearson Education, Inc. 8 -5

Nominal Scale • The numbers (or any other symbol) serve only as labels for identifying and classifying objects. • When used for identification, there is a strict one-to-one correspondence between the numbers and the objects – each number is assigned to only one object and each object has only one number assigned to it (e. g. numbers of foot ball players). • The numbers do not reflect the amount of characteristic possessed by the objects. the • The only permissible operation on the numbers in a nominal scale is counting (description). • Only a limited number of statistics, all of which are based on frequency counts, are permissible, e. g. , percentages, mode, and chi-square. Copyright © 2010 Pearson Education, Inc. 8 -6

Nominal Scale • Example 1: Gender: Males= 1, Females= 2 • Example 2: Sales Zone: Riyadh= 1, Jeddah= 2, Alkhobar= 3 • Example 3: Drink: Pepsi= A, 7 up= B, Miranda= c • Example 4: Product category: Drinks= A, meat= B, Dairy products= C Copyright © 2010 Pearson Education, Inc. 8 -7

Ordinal Scale • A ranking scale in which numbers are assigned to objects to indicate the relative extent to which the objects possess some characteristic from lowest to highest. • Can determine whether an object has more or less of a characteristic than some other object, but not how much more or less. • In marketing research ordinal scales are used to measure relative attitudes, opinions, perceptions, and preferences such as brand ranking. • In addition to the counting operation allowable for nominal scale data, ordinal scales permit the use of statistics based on centiles, e. g. , percentile, and median, and some inferential statistics such as rank-order correlation and Friedman ANOVA. • A problem with ordinal scales is that the difference between categories on the scale is hard to quantify, ie. , exscellent is better than good, but how much is excellent better. Copyright © 2010 Pearson Education, Inc. 8 -8

Ordinal Scale • Example 1: rank your preferences of the following banking services, giving 1 to the first preference, 2 for the second, and 3 for the third: q ATM banking q Telebanking q Digital banking • Example 2: Rank the following Mobile brands according to your buying intention: q Samsung q Lenovo q i. Phone Copyright © 2010 Pearson Education, Inc. 8 -9

Interval Scale • Numerically equal distances on the scale represent equal values in the characteristic being measured. • It permits comparison of the differences between objects. • The location of the zero point is not fixed. Both the zero point and the units of measurement are arbitrary. • In marketing research, attitudinal data obtained from rating scales are often treated as interval data. • It is not meaningful to take ratios of scale values. • Statistical techniques that may be used include all of those that can be applied to nominal and ordinal data, and in addition the arithmetic mean, standard deviation, and other statistics commonly used in marketing research. Copyright © 2010 Pearson Education, Inc. 8 -10

Interval Scale • Example 1: the food variety of the restaurant is: q q q Entirely important Important Neutral Not important Not entirely important • Example 2: I enjoy watching online ads q q q Entirely agree Agree Neutral Disagree Entirely disagree Copyright © 2010 Pearson Education, Inc. 8 -11

Ratio Scale • Possesses absolute rather than relative qualities. • It has an absolute zero point. • It is meaningful to compute ratios of scale values. • Possesses all the properties of the nominal, ordinal, and interval scales. Hence, All statistical techniques can be applied to ratio data. • It is the highest level of measurement. • examples: money, weight, distance, income, age. Copyright © 2010 Pearson Education, Inc. 8 -12

Ratio Scale • Example 1: No. of my children ……. ………. • Examples 2: My monthly salary is SR ……………… • Example 3: In the last 7 days, How many times did you go to the market? ……………. • Example 4: My age …………. Years • Example 5: How often do you go to the barber shop every 3 months? ………………… Copyright © 2010 Pearson Education, Inc. 8 -13

Primary Scales of Measurement Copyright © 2010 Pearson Education, Inc. 8 -14

Copyright © 2010 Pearson Education, Inc. 8 -15