1. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved.

2. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. CHAPTERCHAPTERCHAPTERCHAPTER 1234 0001 897251 00000 15 Coding, Editing, and Preparing Data for Analysis 15-2

3. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Value of Preparing Data for Analysis  Validating, editing, and coding information captured from respondents is a necessary step along the road to providing decision-makers with information they can use to address market opportunities and business problems.  Entering, “combing” or “cleaning,” and tabulating data is a complex, though fascinating process where the raw material collected via the research endeavor is packaged into a format ready for use by decision- makers. 15-3

4. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Essentials of Data Validation Data, when “validated” by a research team covers the following five areas of concern:  Fraud  Screening  Procedure  Completeness  Courtesy 15-4

5. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Essentials of Data Editing When data is “edited” by a research team focuses on the following four questions: 1)Have the answers been asked properly? 2)Have the answers been recorded precisely? 3)Have only qualified respondents been included in the sample? 4)Have all open-end responses been consolidated? 15-5

6. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Editing  Carefully checking survey data for completeness, legibility, consistency, and accuracy.  Most important purpose is to eliminate or at least reduce the number of errors in the raw data.  Two Forms of Error in Raw Survey Data  Interviewer Error  Respondent Error  Two Major Types of Editing  Field Editing  Office Editing

7. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Two Major Types of Editing  Field Editing: Editing done on personal interviews, mall- intercept, and telephone surveys as the data collection takes place. It must occur the same day data gathering occurs.  Office Editing: Editing done at a central location by an office staff after all data collection is finished. It occurs after considerable time has elapsed.

8. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Response Problems and Solutions Potential Problems  Wrong Informant  Return to Sender  Illegible Writing  Incomplete Responses  Damaged Measuring Instrument  Apparently Confused Respondent  Lack of Variance Among Responses  Lack of Consistency Among Responses  Late Responses

9. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Potential Solutions  Follow-up Interviews  Where responses are incomplete or the form was incorrectly filled out, the researchers may send the respondent another form or reinterview the respondent if time permits  Offer a “no valid response” option  Eliminate all unacceptable surveys Response Problems and Solutions – cont’d

10. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Ways To Perform Editing  Personal Editing: Editing performed by a person.  Computer Editing: Editing performed by a computer.

11. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Coding  The process of systematically and consistently assigning each response a numerical score.  The key to a good coding system is for the coding categories to be mutually exclusive and the entire system to be collectively exhaustive.  To be mutually exclusive, every response must fit into only one category.  To be collectively exhaustive, all possible responses must fit into one of the categories.

12. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved.  Coding Missing Numbers: When respondents fail to complete portions of the survey. Whatever the reason for incomplete surveys, researchers must indicate to the computer that there was no response provided by the respondent.  Coding Open-Ended Questions: When open-ended questions are used, researchers must create categories. All responses must fit into a category, once all responses have been returned. Furthermore, similar responses should fall into the same category. Coding – cont’d

13. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Coding – cont’d  Precoded Questionnaires: Sometimes researchers place codes on the actual questionnaire, which simplifies data entry.  There are Two Sets of Codes:  One set codes individual responses.  The second set of codes is for individual questions.

14. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved.  Codebook: Contains the instructions for the people who code survey data. It is the blueprint for proper data coding.  The codebook typically includes:  Column Number  Variable Number  Variable Name  Question Number  Coding Instructions Coding – cont’d

15. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Entering Data  If data entry is not instantaneous, then data-entry operators (or keyboard operators) are needed to input survey data into the computer.  Problems can occur during data entry tasks, such as transposing numbers and inputting an infeasible code. It is a good idea to have someone check the data- entry operator’s work.  Optical-Scanning Devices: Are data-processing machines that electronically read survey answers that are in a prescribed form, such as numbers, codes, or words.  With rapidly advancing technologies, data entry will become ever more streamlined.

16. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Data Tabulation  Tabulation: The organized arrangement of data in a table format that is easy for the researcher to read and understand.  Researchers tabulate the data to count the number of responses to each question.  Simple Tabulation: The tabulating of results of only one variable to inform the researcher how often each response was given.  Cross Tabulation: A statistical technique that involves tabulating the results of two or more variables simultaneously to inform the researcher how often each response was given.

17. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Reviewing Tabulations Researchers need to review the study’s tabulations to determine whether or not the data contains any additional mistakes before they begin running statistical tests. This may be partially accomplished by running frequency distributions. Frequency Distribution: A distribution of data that summarizes the number of times a certain value of a variable occurs and is expressed in terms of percentages.

18. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Essentials of Data Coding Data, when “coded” by a research team involves assigning a “value” (normally a number – e.g. “1” or “2”) to the responses to each question contained in the survey. AN EXAMPLE: The two responses which follow a question such as: “What is your gender?” would have a “1” assigned to the category “Female” and “2” assigned to the category “Male”. 15-6

19. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. How to Handle Open-Ended Questions There are four stages to coding open-end questions: 1)Brainstorm a list of possible responses and create a list. Assign a value to each of the responses. 2)Consolidate the responses into response category which exhibit shared meaning. 3)Assign values to data which has been captured by the survey instrument, as well as data which has been omitted by the respondent. 4)Assign a coded value to each response. 15-7

20. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Master Code Form: An Example FAST-FOOD OPINION SURVEY This questionnaire pertains to a project being conducted by a marketing research class at The University of Memphis. The purpose of this project is to better understand the attitudes and opinions of consumers toward fast-food restaurants. The questionnaire will take only 10-15 minutes to complete, and all responses will remain strictly confidential. Thank you for your help on this project. 15-8a 1.Below is a listing of various fast-food restaurants. How many of these restaurants would you say you visited in the past two months? Check as many as may apply. Taco Bell01Church’s Fried Chicken08 Hardee’s02McDonald’s09 Kentucky Fried Chicken03Burger King10 Wendy’s04Back Yard Burgers11 Rally’s05Arby’s12 Popeye’s Chicken06Sonic13 Krystal’s07Other, please specifySee code sheet Have not visited any of these establishments 20 √

21. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Master Code Form: An Example 15-8b 2.In a typical month, how many times would you say you visit a fast-food restaurant, such as the ones indicated above? (X ONE BOX) One  Two  Three  Four  Five  Six  Seven or more  1234567 √

22. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Master Code Form: An Example 15-8c 3.On your last visit to a fast-food restaurant, what was the dollar amount you spent on food and beverages? Under $2o 1$8.01-$10.00o 5 $2.01-$4.00o 2$10.01-$12.00o 6 $4.01-$6.00o 3More than $12o 7 $6.01-$8.00o 4Don’t Remembero 8 √

23. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. The Essentials of Data Entry When data is “entered” by a research it’s normally done in any one or a combination of the following four ways: 1)Key driven devices like a computer (PC). 2)Touch Screen Technology. 3)Light Pens. 4)Scanning Technology e.g. Bubble Shop 15-9

24. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Data Tabulation: One-Way Tabulation When a research team performs a “one-way” tabulation they focus on a single variable operating in the research study. 15-10

25. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Frequency Distribution: An Example 15-11a 5.In the past TWO WEEKS, which fast-food restaurants in your area have you had food or beverage from? (27) (DO NOT READ-MULTIPLE RESPONSE) FrequencyPercentage 1.Andy’s3.7 2.Arby’s256.2 3.Back Yard Burgers266.4 4.Burger King4811.9 5.Church’s Fried Chicken3.7 6.Hardee’s225.4 7.Kentucky Fried Chicken399.7 8.McDonald’s13533.4

26. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Frequency Distribution: An Example 15-11b FrequencyPercentage 9. Sonic4611.4 10. Subway143.5 11. Taco Bell6716.6 12. Wendy’s8420.8 13. Other4310.6 14. Refused1.2 15. Don’t know61.5 16. None5212.9 17. Pizza Hut215.2 18. Rally’s143.5 19. Captain D’s92.2 Total qualified404100

27. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Data Tabulation: Cross-Tabulation When a research team performs a “cross- tabulation” they focus on two or more variables contained in questions in the research study. 15-12

28. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Cross-Tabulation: An Example 15-13 Q2 Female 1 Male 2 Row Total None 0112.5 One 1272350 11.8 Two 2253358 13.6 Three 3162541 9.6 Four 4383270 16.5 Five 5121426 6.1 Six 6191534 8.0 Seven or more 77074144 33.9 Q2 Visits per Month by Q1520 Gender Q1520Page 1 of 1 Count Column 208 217 425 Total 48.9 51.1 100.0 Number of Missing Observations: 18

29. 1995 7888 4320 000 000001 00023 Copyright © 2003 by The McGraw-Hill Companies, Inc. All rights reserved. Summary of Learning Objectives  Illustrate the process of preparing data for preliminary analysis.  Demonstrate the procedure for assuring data validation.  Illustrate the process of editing and coding data obtained through survey methods.  Acquaint the user with data entry procedures.  Illustrate a process for detecting errors in data entry.  Discuss techniques used for data tabulation and data analysis. 15-15