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Lecture 17

MKT 473 Lecture 17: MKT 473 Chapter 17 & 18 Notes

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MKT 473

MKT 473 Chapter 17 & 18 Notes Overview of the Data Analysis Procedure • The key steps: 1. Validation and editing • Validation: process of ascertaining that interviews were actually conducted as specified • Editing: process of ascertaining that questionnaires were filled out properly and completely • Skip pattern: sequence in which later questions are asked, based on a respondent’s answer to an earlier question or questions 2. Coding 1. Coding: process of grouping and assigning numeric codes to the various responses to a question 3. Data entry • Data entry: process of converting information to an electronic format • Intelligent data entry: form of data entry in which the information being entered into the data entry device is checked for internal logic • Scanning: form of data entry in which responses on questionnaires are read in automatically by the data entry device 4. Logical cleaning of data • Clean the data: check for data entry errors or data entry inconsistencies • Logical or machine cleaning: final computerized error check of data • Error check routines: computer programs that accept instructions from the user to check for logical errors in the data • Marginal report: computer-generated table of the frequencies of the responses to each question, used to monitor entry of valid codes and correct use of skip patterns 5. Tabulation and statistical analysis • One-way frequency tables: table showing the number of respondents choosing each answer to a survey question • Cross tabulation tables: examination of the responses to one question relative to the responses to one or more other questions The Coding Process 1. List responses 2. Consolidate responses 3. Set codes 4. Enter codes 1. Read responses to an individual open-ended questions on questionnaires 2. Match individual responses with consolidated list of response categories Text Analytics • Text analytics is a technology that turns unstruc
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