DATA PREPARATION AND DESCRIPTION Chapter 15 McGraw-Hill/IrwinCopyright © 2014 by The McGraw-Hill Companies, Inc. All rights reserved.
15-2 Learning Objectives Understand... The importance of editing the collected raw data to detect errors and omissions. How coding is used to assign number and other symbols to answers and to categorize responses. The use of content analysis to interpret and summarize open questions.
15-3 Learning Objectives Understand... Problems with and solutions for “don’t know” responses and handling missing data. The options for data entry and manipulation.
15-4 Pull Quote “Pattern thinking, where you look at what’s working for someone else and apply it to your own situation, is one of the best ways to make big things happen for you and your team.” David Novak, chairman and CEO, Yum! Brands, Inc.
15-5 Data Preparation in the Research Process
15-6 Monitoring Online Survey Data Online surveys need special editing attention. CfMC provides software and support to research suppliers to prevent interruptions from damaging data.
15-7 Editing Criteria Consistent Uniformly entered Arranged for simplification Complete Accurate
15-8 Field Editing Field editing review Entry gaps identified Callbacks made Results validated
15-9 Central Editing Be familiar with instructions given to interviewers and coders Do not destroy the original entry Make all editing entries identifiable and in standardized form Initial all answers changed or supplied Place initials and date of editing on each instrument completed
15-10 Sample Codebook
15-11 Precoding
15-12 Coding Open-Ended Questions 6. What prompted you to purchase your most recent life insurance policy? _______________________________
15-13 Coding Rules Categories should be Categories should be Appropriate to the research problem Exhaustive Mutually exclusive Derived from one classification principle
15-14 Content Analysis
15-15 Types of Content Analysis Syntactical Propositional Referential Thematic
15-16 Open-Question Coding Locus of Responsibility Mentioned Not Mentioned A. Company____________________________ B. Customer____________________________ C. Joint Company- Customer____________________________ F. Other____________________________ Locus of Responsibility Frequency (n = 100) A. Management 1. Sales manager 2. Sales process 3. Other 4. No action area identified B. Management 1. Training C. Customer 1. Buying processes 2. Other 3. No action area identified D. Environmental conditions E. Technology F. Other
15-17 Proximity Plot
15-18 Handling “Don’t Know” Responses Question: Do you have a productive relationship with your present salesperson? Years of Purchasing YesNoDon’t Know Less than 1 year10%40%38% 1 – 3 years years or more6030 Total 100% n = % n = % n = 200
15-19 Data Entry Database Programs Optical Recognition Digital/ Barcodes Voice recognition Keyboarding
15-20 Missing Data Solutions Listwise Deletion Pairwise Deletion Replacement
15-21 Key Terms Bar code Codebook Coding Content analysis Data entry Data field Data file Data preparation Data record Database Don’t know response Editing Missing data Optical character recognition Optical mark recognition Precoding Spreadsheet Voice recognition
ADDITIONAL DISCUSSION OPPORTUNITIES Chapter 15
15-23 CloseUp: Dirty Data Invalid: entry errors Incomplete: missing, siloed, turf wars Inconsistent: across databases Incorrect: lost, falsified, outdated Solutions: Data Steward, Data Protocols, Error Detection Software
15-24 Snapshot: CBS labs 39 Million Visitors Show Screenings Dial Testing Surveys Focus Groups
15-25 PicProfile: Content Analysis QSR’s XSight software for content analysis.
15-26 Snapshot: Netnography Data Posted on Internet & intranets Product & company reviews Employee experiences Message board posts Discussion forum posts
15-27 Research Thought Leader “ The goal is to transform data into information, and information into insight. Carly Fiorina former president and chairwoman, Hewlett-Packard Co
15-28 PulsePoint: Research Revelation 55 The percent of white-collar workers who answer work-related calls or e- mail after work hours.
DATA PREPARATION AND DESCRIPTION Chapter 15
15-30 Photo Attributions