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Data Preparation for Analysis

Data Preparation for Analysis. Chapter 11, Student Edition. Learning Objectives. Explain the purpose of the editing process Define what coding is Describe the kinds of information contained in a codebook Describe common methods for cleaning the data file

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Data Preparation for Analysis

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  1. Data Preparation for Analysis Chapter 11, Student Edition MR/Brown & Suter

  2. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  3. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  4. Learning Objective 1 • Editing – the inspection and correction of the data received from each element of the sample (or census) • During the editing process, it must be decided what to do about cases with incomplete answers, obviously wrong answers, and answers that reflect a lack of interest MR/Brown & Suter

  5. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  6. Learning Objective 2 • Coding – the process of transforming raw data into symbols (usually numbers) that can be utilized for analysis • Coding Closed-ended Items • Examples • 1 = Female, 2 = Male • 1 = Unfavorable to 7 = Favorable • Coding Open-ended Items • Factual open-ended items are highly structured and easy to code • Exploratory open-ended items are less structured and allow for multiple responses making it more difficult to code MR/Brown & Suter

  7. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  8. SPORTING GOODS SURVEY • Please answer the following questions about buying sporting goods over the internet: • During the past year, what percentage of the sporting goods you purchased were ordered through the internet? • ________ percent • 2. How willing are you to purchase merchandise offered through the Avery Sporting Goods web site? • Not at all willing Somewhat willing Very willing • 3. Please provide some reasons why someone might not want to purchase sporting goods over the internet: Learning Objective 3 MR/Brown & Suter

  9. Learning Objective 3 MR/Brown & Suter

  10. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  11. Learning Objective 4 • Blunder • An error that arises during editing, coding or data entry • Blunders are usually due to researcher carelessness • Blunders Can Be Located By • Examining frequency distributions on all variables • Checking a sample of questionnaires against the data file • Double-entry of data in which data are entered into two separate data files and then compared for discrepancies (preferred) • Optical scanning can be used to “read” responses • Nonresponse/Missing Data Should Also Be Investigated MR/Brown & Suter

  12. Learning Objectives • Explain the purpose of the editing process • Define what coding is • Describe the kinds of information contained in a codebook • Describe common methods for cleaning the data file • Discuss options for dealing with missing data in analyses MR/Brown & Suter

  13. Learning Objective 5 • Eliminate the Case with the Missing Items from All Further Analyses • Eliminate the Case with the Missing Items from Analyses Using the Variable • Substitute Values for the Missing Items • Contact the Respondent Again MR/Brown & Suter

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