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Chapter Thirteen Coding, Editing and Presenting Data, and Preliminary data Analysis Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-1 Learning Objectives Illustrate the process of preparing the data for 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 the process for detecting errors in data entry. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-2 Learning Objectives Discuss techniques used for data tabulation. Understand the mean, median and mode as measures of central tendency. Understand the range and standard deviation of a frequency distribution as measures of dispersion. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-3 Introduction Data preparation is the process of taking data and preparing it for conversion into information. Data validation is the process of determining whether a survey’s interviews or observations were conducted correctly and are free of fraud or bias. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-4 The Essentials of Data Validation Data, when ‘validated’ by a research team covers the following five areas of concern: 1. 2. 3. 4. 5. Fraud; Screening; Procedure; Completeness; Courtesy. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-5 Data Editing Data editing is the process of checking the data for mistakes made by the interviewer or the respondent. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-6 Data Editing Need to check: 1. 2. 3. 4. Asking of questions Recording of answers Screening of respondents Recording and coding of open ended questions. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-7 Data Coding Data coding is the process of grouping and assigning value to the responses from the survey instrument. Incorporate coding into questionnaire design where possible. Use numeric codes. Assign codes to missing data. Open ended questions need to be coded for data entry. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-8 The Master Code Form—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 towards 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. 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 Bell 01 Church’s Fried Chicken 08 Hardee’s 02 McDonald’s 09 Kentucky Fried Chicken 03 Burger King 10 Wendy’s 04 Back Yard Burgers 11 Rally’s 05 Arby’s 12 Popeye’s Chicken 06 Sonic 13 Krystal’s 07 Other, please specify Have not visited any of these establishments Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex See code sheet 20 13-9 How to Handle Open-Ended Questions There are four stages to coding openend 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 categories 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. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-10 Data Entry Data entry is the process of the direct input of the coded data into some package to analyse, manipulate and transform the data into useful information. Can be entered directly into the computer Entered manually Scanned Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-11 Error Detection Error detection is the process of ensuring that the data is error-free. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-12 Data Description Data description is the process of describing the data sample so that general patterns of responses and respondent profiles are revealed. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-13 Data Tabulation: One-Way Tabulation The process of counting the number of observations/cases that analysts classify into certain categories. When a research team performs a ‘one-way’ tabulation they focus on a single variable operating in the research study. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-14 Frequency Distribution—An Example Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-15 Data Tabulation: Cross-tabulation A ‘cross-tabulation’ focuses on two or more variables contained in questions in the research study. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-16 Cross-tabulation—Example Brand use most often * Gender Crosstabulation Brand us e most often LG MOTOROLA NOKIA SAMSUNG SONY ERICKSON Total Count % within Gender Count % within Gender Count % within Gender Count % within Gender Count % within Gender Count % within Gender Gender Male Female 8 18 7.7% 24.3% 13 19 12.5% 25.7% 51 26 49.0% 35.1% 12 9 11.5% 12.2% 20 2 19.2% 2.7% 104 74 100.0% 100.0% Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex Total 26 14.6% 32 18.0% 77 43.3% 21 11.8% 22 12.4% 178 100.0% 13-17 Measures of Central Tendency There are three primary measures of central tendency: 1. The Mean 2. The Mode 3. The Median Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-18 Desired Measures of Central Tendency and Dispersion Measures of Central Tendency: 1. Mean is the arithmetic average of all the data responses in the sample. 2. Mode is the most common value in the set of responses to a question. 3. Median occurs where half of the data is above the statistic value and half is below. This is the middle value of a rank ordered distribution. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-19 Measures of Dispersion There are two primary measures of dispersion: 1. The Range 2. The Standard Deviation The variance is the average squared deviation about the mean. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-20 Desired Measures of Dispersion Measures of Dispersion Frequency distribution is a summary of how many times each raw response was recorded. Range is the spread of the data. Estimated sample standard deviations specify the degree of variation in the data responses. Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-21 It is important to note the following: If a nominal scale is used analysis of data can only be done using modes and frequency distributions. If ordinal scales are used analysis of data can be done using medians and ranges (plus modes and frequency distributions). If interval or ratio scales are used analysis of data can be done through the use of sample means and estimated standard deviations as the sample statistic (plus the above). Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-22 Analysis of Data Programs such as SPSS can be used to analyse data. Frequencies. Cross tabs, measures of dispersion And more… Copyright 2007 McGraw-Hill Pty Ltd PPTs t/a Marketing Research 2e by Lukas, Hair, Bush and Ortinau Slides prepared by Judy Rex 13-23