1. Marketing Research Aaker, Kumar, Day Seventh Edition Instructor’s Presentation Slides

2. Chapter Sixteen Fundamentals of Data Analysis

3. © Marketing Research 7th EditionAaker, Kumar, Day Data Analysis A set of methods and techniques used to obtain information and insights from data Helps avoid erroneous judgements and conclusions Can constructively influence the research objectives and the research design

4. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis Data editing Coding Statistically adjusting the data

5. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Data Editing Identifies omissions, ambiguities, and errors in responses Conducted in the field by interviewer and field supervisor and by the analyst prior to data analysis

6. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Problems Identified With Data Editing Interviewer Error Omissions Ambiguity Inconsistencies Lack of Cooperation Ineligible Respondent

7. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Coding Coding closed-ended questions involves specifying how the responses are to be entered Open-ended questions are difficult to code Lengthy list of possible responses is generated

8. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Statistically Adjusting the Data + Weighting Each response is assigned a number according to a pre-specified rule Makes sample data more representative of target population on specific characteristics Modifies number of cases in the sample that possess certain characteristics Adjusts the sample so that greater importance is attached to respondents with certain characteristics

9. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Statistically Adjusting the Data + Variable Re- specification Existing data is modified to create new variables Large number of variables collapsed into fewer variables Creates variables that are consistent with study objectives Dummy variables are used (binary, dichotomous, instrumental, quantitative variables) Use (d-1) dummy variables to specify (d) levels of qualitative variable

10. © Marketing Research 7th EditionAaker, Kumar, Day Preparing the Data for Analysis (Contd.) Statistically Adjusting the Data + Scale Transformation Scale values are manipulated to ensure comparability with other scales Standardization allows the researcher to compare variables that have been measured using different types of scales Variables are forced to have a mean of zero and a standard deviation of one Can be done only on interval or ratio scaled data

11. © Marketing Research 7th EditionAaker, Kumar, Day Simple Tabulation Consists of counting the number of cases that fall into various categories Use of Simple Tabulation Determine empirical distribution (frequency distribution) of the variable in question Calculate summary statistics, particularly the mean or percentages Aid in "data cleaning" aspects

12. © Marketing Research 7th EditionAaker, Kumar, Day Frequency Distribution Reports the number of responses that each question received Organizes data into classes or groups of values Shows number of observations that fall into each class Can be illustrated simply as a number or as a percentage or histogram Response categories may be combined for many questions Should result in categories with worthwhile number of respondents

13. © Marketing Research 7th EditionAaker, Kumar, Day Descriptive Statistics Statistics normally associated with a frequency distribution to help summarize information in the frequency table Measures of central tendency mean, median and mode Measures of dispersion (range, standard deviation, and coefficient of variation) Measures of shape (skewness and kurtosis)

14. © Marketing Research 7th EditionAaker, Kumar, Day Analysis for Various Population Subgroups Differences between means or percentages of two subgroup responses can provide insights Difference between means is concerned with the association between two questions Question upon which means are based are intervally scaled

15. © Marketing Research 7th EditionAaker, Kumar, Day Cross Tabulations Statistical analysis technique to study the relationships among and between variables Sample is divided to learn how the dependent variable varies from subgroup to subgroup Frequency distribution for each subgroup is compared to the frequency distribution for the total sample The two variables that are analyzed must be nominally scaled

16. © Marketing Research 7th EditionAaker, Kumar, Day Factors Influencing the Choice of Statistical Technique Type of Data Classification of data involves nominal, ordinal, interval and ratio scales of measurement Nominal scaling is restricted to the mode as the only measure of central tendency Both median and mode can be used for ordinal scale Non-parametric tests can only be run on ordinal data Mean, median and mode can all be used to measure central tendency for interval and ratio scaled data

17. © Marketing Research 7th EditionAaker, Kumar, Day Factors Influencing the Choice of Statistical Technique (Contd.) Research Design Dependency of observations Number of observations per object Number of groups being analyzed Control exercised over variable of interest Assumptions Underlying the Test Statistic If assumptions on which a statistical test is based are violated, the test will provide meaningless results

18. © Marketing Research 7th EditionAaker, Kumar, Day Overview of Statistical Techniques Univariate Techniques Appropriate when there is a single measurement of each of the 'n' sample objects or there are several measurements of each of the `n' observations but each variable is analyzed in isolation Nonmetric - measured on nominal or ordinal scale Metric-measured on interval or ratio scale Determine whether single or multiple samples are involved For multiple samples, choice of statistical test depends on whether the samples are independent or dependent

19. © Marketing Research 7th EditionAaker, Kumar, Day Overview of Statistical Techniques (Contd.) Multivariate Techniques A collection of procedures for analyzing association between two or more sets of measurements that have been made on each object in one or more samples of objects Dependence or interdependence techniques

20. © Marketing Research 7th EditionAaker, Kumar, Day Overview of Statistical Techniques (Contd.) Multivariate Techniques (Contd.) Dependence Techniques One or more variables can be identified as dependent variables and the remaining as independent variables Choice of dependence technique depends on the number of dependent variables involved in analysis

21. © Marketing Research 7th EditionAaker, Kumar, Day Overview of Statistical Techniques (Contd.) Multivariate Techniques (Contd.) Interdependence Techniques Whole set of interdependent relationships is examined Further classified as having focus on variable or objects

22. © Marketing Research 7th EditionAaker, Kumar, Day Overview of Statistical Techniques (Contd.) Why Use Multivariate Analysis? To group variables or people or objects To improve the ability to predict variables (such as usage) To understand relationships between variables (such as advertising and sales)