1. CHAPTER 13
Data Processing, Basic Data Analysis, and the Statistical Testing Of Differences
Copyright © 2000 by John Wiley & Sons, Inc.

2. 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.

3. 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?

4. 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

5. 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

6. 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.

7. 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

8. 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

9. 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

10. 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

11. 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

12. 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

13. 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.

14. 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.

15. 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.

16. The End
Copyright © 2000 by John Wiley & Sons, Inc.