Data Processing, Basic Data Analysis, and the Statistical Testing of Differences CHAPTER thirteen Copyright © 2000 South-Western College Publishing Co.

Learning Objectives 1. 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 crosstabulated. 4. To understand how to state and test hypotheses. 5. To describe several common statistical tests of differences.

Checking for interviewer mistakes To understand the importance and nature of quality control. STEP ONE: VALIDATION and EDITING Validation The process of ascertaining that interviews actually were conducted as specified. Editing Checking for interviewer mistakes 1. Did the interviewer ask or record answers for certain questions? 2. Skip patterns followed? 3. Open-ended responses checked?

Grouping and assigning numeric codes to the responses To understand the data-entry process and data-entry alternatives. STEP TWO: CODING Coding Defined Grouping and assigning numeric codes to the responses The Coding Process 1. Listing responses 2. Consolidating responses 3. Setting codes 4. Entering codes

Intelligent Versus Dumb Entry To understand the data-entry process and data-entry alternatives. STEP THREE: DATA ENTRY Intelligent Versus Dumb Entry Logical checking of information computers The Data Entry Process The mechanics of the process Optical Scanning A device that can “read” responses on questionnaires

Machine Cleaning of Data A final computerized error check of data. To understand the data-entry process and data-entry alternatives. STEP FOUR: MACHINE CLEANING DATA Machine Cleaning of Data A final computerized error check of data. Marginal Report A computer-generated table of the frequencies of the responses to each question to monitor entry of valid codes and correct use of skip patterns.

One Way Frequency Tables To learn how surveys are tabulated and crosstabulated. STEP FIVE: TABULATION and ANALYSIS of SURVEY RESULTS One 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 answering Selecting the Base for One-Way Frequency Tables Showing Results from Multiple-Choice Questions Cross-Tabulations

4. Multiple row, three-dimensional bar charts To learn how surveys are tabulated and crosstabulated. GRAPHIC PRESENTATIONS OF DATA Line Charts Pie Charts Bar Charts 1. Plain bar chart 2. Clustered bar charts 3. Stacked bar charts 4. Multiple row, three-dimensional bar charts

Measures of Central Tendency Mean Mode Median Measures of Dispersion To learn how surveys are tabulated and crosstabulated. DESCRIPTIVE STATISTICS Measures of Central Tendency Mean Mode Median Measures of Dispersion Standard deviation Variance Range Means, Percentages, and Statistical Tests

Mathematical differences Statistical significance To understand how to state and test hypothesis. STATISTICAL SIGNIFICANCE It is possible for numbers to be different in a mathematical sense but not statistically different in a statistical sense. Mathematical differences Statistical significance Managerially important differences

Stating the Hypothesis Null hypothesis: Ho Alternative hypothesis: Ha To understand how to state and test hypothesis. HYPOTHESIS TESTING Hypothesis An assumption that a researcher makes about some characteristic of the population. Stating the Hypothesis Null hypothesis: Ho Alternative hypothesis: Ha Choose the Appropriate Test Statistic Developing a Decision Rule Calculating the Value of the Test Statistic Stating the Conclusion

Independent Versus Related Samples Independent samples To understand how to state and test hypothesis. Independent Versus Related Samples Independent samples Measurement of a variable in one population has no effect on the measurement of the other variable Related Samples Measurement of a variable in one population may influence the measurement of the other variable. Degrees of Freedom The number of observations minus the number of constraints. HYPOTHESIS TESTS

Chi-Square Test of a Single Sample To describe several common statistical tests of differences. GOODNESS OF FIT Chi-Square To determine whether an observed pattern of frequencies corresponds to an “expected” pattern. Chi-Square Test of a Single Sample Chi-Square Test of Two Independent Samples Association between two or more variables.

Test of a Proportion, One Sample Phenomena expressed as percentages To describe several common statistical tests of differences. HYPOTHESES ABOUT PROPORTIONS Test of a Proportion, One Sample Phenomena expressed as percentages Tests of Differences Between Two Proportions, Independent Samples Management may be interested in the difference between the proportions of people in two different groups that engage in a certain activity or have a certain characteristic.

To describe several common statistical tests of differences. p - VALUES AND SIGNIFICANCE TESTING P -Value The exact probability of getting a computed test statistic that was largely due to chance. The smaller the p-value, the smaller the probability that the observed result occurred by chance.

The End Copyright © 2000 South-Western College Publishing Co.