DATA COLLECTION & ANALYSIS APPLICATION

1. DATA COLLECTION& ANALYSIS APPLICATION Principles of Marketing Week 09

2. Learning Objectives Data Preparation • Process of data preparation for analysis • Validation, editing, and coding of survey data • Data entry procedures • How to detect errors • Data tabulation approaches

3. Overview of data preparation & analysis

4. Data preparation • Process of converting information from a questionnaire so it can be utilized • Four Steps: • Data Validation • Editing and Coding • Data Entry • Data Tabulation

5. Data preparation • Four Steps: • Data Validation • Determine if the survey’s interview or observations were conducted correctly and free of interviewer fraud or bias. • Need to check for factors such as • Courtesy • Screening • Procedure • Completeness

6. Data preparation • Four Steps: • Editing and Coding • Editing • The process that checks the data for mistakes made by either the interviewer or respondent • Areas to check: • Asking proper questions • Accurate recording of answers • Correct screening questions • Reponses to open ended questions

7. Data preparation • Four Steps: • Editing and Coding • Editing

8. Data preparation • Four Steps: • Editing and Coding • Coding • Grouping and assigning values to various responses from the survey instrument • Coding should be: • Numerical (from 0-9) • Well planned and constructed questionnaires reduce time spent on coding • Numeric codes should be designed into the questionnaire from the beginning. • If questionnaires do not use coded responses a master coding system must be established

9. Data preparation • Four Steps: • Editing and Coding • Example of a Master Code Sheet

10. Data preparation • Four Steps: • Editing and Coding • Coding • Coding open ended questions is a four-step process • Generate a master list of potential responses • Assign values to the responses • Specify a numerical value as a code • Assign a coded value to each response

11. Data preparation • Four Steps: • Data Entry • 4 Major Ways • Computer (Most popular) • Scanner • Touch Scanner • Light Pen

12. Data preparation • Four Steps: • Data Entry

13. Data preparation • Four Steps: • Data Entry • Error Detection : First Step • Determine if the software used for data entry and tabulation includes error editing routines • Identify the wrong type of data • Prepare a printed representation of the data entered • To produce a data/column list of the data • To find individual questionnaires and verify the proper response (code)

14. Data preparation • Four Steps: • Data Tabulation • Process of counting the numbers of observations classified into certain categories • One way tabulation • Cross tabulation

15. Data preparation • Four Steps: • Data Tabulation • One Way Tabulation Purposes • Determine the frequency of non response to individual questions • Locate errors or blunder in data entry • Calculate summary statistics such as means, standard deviations, range, etc. • Communicate results of research project

16. Data preparation • Four Steps: • Data Tabulation • Cross Tabulation • Determine whether variables differ when compared across sample subgroups. • Results show frequencies and percentages for both rows and columns.

17. Data preparation • Four Steps: • Data Tabulation • Issues to be considered • Judgment of the analyst—selection of variables (questions) to use examining relationships • Demographic variables or lifestyle / psychographic characteristics are the starting point in developing cross-tabulations. • Technique is simple but findings may be difficult to interpret • Keep research objectives in mind when constructing and using tables • Spreadsheets help

18. Data preparation • Four Steps: • Data Tabulation • Descriptive Statistics • Summarize and describe data obtained from a sample of respondents

19. Data preparation • Four Steps: • Data Tabulation • Descriptive Statistics • Summarize and describe data obtained from a sample of respondents

20. HOMEWORK • In this week’s homework you will be expected to complete the following: • Questionnaire Design • Redesign the questionnaire from last week’s homework and give it out to a minimum of 75 people. • Review answers and began the data analysis portion of your final project. Bring to class for review week 10.

21. FINAL PROJECT SPECS • The final project is the culminating academic endeavor of the class’s research over the quarter. • It will provide you with the opportunity to explore a problem or issue of particular personal or professional interest and to address it in a thorough focused study and applied research. • This project should demonstrate your ability to synthesize and apply the knowledge and skills acquired through the class, and it should not only exemplify your ability to think critically, but should utilize the variety of research methods introduced to come to a cohesive and logical conclusion.

22. FINAL PROJECT SPECS • Sections • Executive Summary • Industry Analysis • Marketing Research • Hypothesis/Problem Statement/Purpose • Research Objectives • Limitations • Methodology • Sample Questionnaire • Data Analysis • Conclusions