Lecture Marketing research - Chapter 12: Data Processing, fundamental data analysis, and statistical testing of differences

In this chapter you will: Develop an understanding of the importance and nature of quality control checks, understand the data entry process and data entry alternatives, learn how surveys are tabulated and cross-tabulated, understand the concept of hypothesis development and how to text hypotheses.
Nội dung trích xuất từ tài liệu:
Lecture Marketing research - Chapter 12: Data Processing, fundamental data analysis, and statistical testing of differences Learning ObjectivesCHAPTER Twelve Data Processing, Fundamental Data Analysis, and Statistical Testing of Differences Copyright © 2004 John Wiley & Sons, Inc. Learning Objectives Learning Objectives1. To develop an understanding of the importance and nature of quality control checks.2. To understand the data entry process and data entry alternatives.3. To learn how surveys are tabulated and cross- tabulated.4. To understand the concept of hypothesis development and how to text hypotheses. Learning Objectives To get an overview of the dataThe Data AnalysisProcedure analysis procedure. Five Step Procedure for Data Analysis: Step One: Validation and editing (quality control) Step Two: Coding Step Three: Data Entry Step Four: Machine Cleaning of Data Step Five: Tabulation and Statistical Analysis Learning Objectives Validation and Editing To understand the importance and nature of quality control checks.ValidationThe process of ascertaining that interviews actually wereconducted as specified.EditingChecking for interviewer mistakes 1. Did the interviewer ask or record answers for certain questions? 2. Questionnaires are checked to make sure Skip patterns are followed. 3. Responses to open-ended responses are checked. Learning Objectives Data Entry To understand the data-entry process and data-entry alternatives.Intelligent Data Entry The checking of information being entered for internal logic by either that data entry device or another device connected to it.The Data Entry Process The mechanics of the process. The validated, edited, and coded questionnaires are given to a data entry operator. The process of going directly from the questionnaire to the data entry device and storage medium is more accurate and efficient. Learning Objectives Tabulation of To learn how surveys are tabulated. Survey ResultsOne Way Frequency Tables A table showing the number of responses to each answer.Base for Percentages 1. Total respondents 2. Number of people asked the question 3. Number of people answering the questionSelecting the Base for One-Way Frequency TablesShowing Results from Multiple-Choice Questions Learning Objectives Tabulation of To learn how to set up and Survey Results interpret crosstabulations.Cross-TabulationsExamination of the responses of one question relative toresponses to one or more other questions.Provides a powerful and easily understood approach to thesummarization and analysis of survey research results. Learning ObjectivesGraphic Representations To comprehend the basic of Data techniques of statistical analysis.Line ChartsThe simplest form of graphs.Pie ChartsAppropriate for displaying marketing research results in awide range of situations.Bar Charts 1. Plain bar chart 2. Clustered bar charts 3. Stacked bar charts 4. Multiple row, three-dimensional bar charts Learning Objectives To comprehend the basicDescriptive Statistics techniques of statistical analysis. Measures of Central Tendency • Mean h fiXi I=1 X = where n fi = the frequency of the ith class Xi = the midpoint of that class h = the number of classes n = the total number of observations Learning Objectives To comprehend the basicDescriptive Statistics techniques of statistical analysis. • Mean The sum of the values for all observation of a variable divided by the number of observations • Median The observation below which 50 percent of the observations fall. • Mode The value that occurs most frequently Learning Objectives To comprehend the basicDescriptive Statistics techniques of statistical analysis. Measures of Dispersion Variance The sums of the squared deviations from the mean divided by the number of observations minus one. The same formula as standard deviation with the square-root sign removed. Range The maximum value for a variable minus the minimum value for that variable Learning Objectives To comprehend the basicDescriptive Statistics techniques of statistical analysis. Measures of Dispersion Standard deviation Calculated by: • subtracting the mean of a series from each value in a series • squaring each result • summing them • dividing by the number of items minus 1 • and taking the square root of this value. Learning Objectives To compre ...