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PASW Statistics 18 Guide to Data Analysis

By Marija J. Norusis, Inc. SPSS Inc.

Published by Pearson

Published Date: Mar 1, 2010

Description

The PASW Statistics 18 Guide to Data Analysis is a friendly introduction to both data analysis and PASW Statistics 18 (formerly SPSS Statistics), the world’s leading desktop statistical software package. Easy-to-understand explanations and in-depth content make this guide both an excellent supplement to other statistics texts and a superb primary text for any introductory data analysis course. With this book, you’ll learn how to describe data, test hypotheses, and examine relationships using PASW.

Author Marija Norušis incorporates a wealth of real data, including the General Social Survey and studies of Internet usage, opinions of the criminal justice system, marathon running times, library patronage, and the importance of manners, throughout the examples and expanded chapter exercises. This unique combination of examples, exercises, and contemporary data gives you hands-on experience in analyzing data and makes learning about data analysis and statistical software relevant, unintimidating, and even fun!

A data CD-ROM is included with this book.

Table of Contents

PART 1. GETTING STARTED WITH PASW STATISTICS

 

1. Introduction

About This Book

            Getting Started with PASW Statistics

            Describing Data

            Testing Hypotheses

            Examining Relationships

            Lets Get Started

 

2. An Introductory Tour of PASW Statistics

Starting PASW Statistics

            Help Is Always at Hand

Copying the Data Files

Opening a Data File

Statistical Procedures

            The Viewer Window

            Viewer Objects

The Data Editor Window

            Entering Non-Numeric Data

            Clearing the Data Editor without Saving Changes

The PASW Statistics Online Tutorial

The PASW Statistics Toolbar

The PASW Statistics Help System

            Contextual Help

What’s Next?

 

3. Sources of Data

Know Your Data

Survey Data

            Asking the Question

            Measuring Time

            Selecting Participants

            Selecting a Sample

            General Social Survey

            Random-Digit Dialing

            Internet Surveys

Designing Experiments

            Random Assignment

            Minimizing Bias

Summary

What’s Next?

Exercises

 

PART 2 DESCRIBING DATA

 

4. Counting Responses

Describing Variables

            A Simple Frequency Table

            Sorting Frequency Tables

            Pie Charts

            Bar Charts

Summarizing Internet Time

            Histograms

            Mode and Median

            Percentiles

Summary

What’s Next?

How to Obtain a Frequency Table

            Format: Appearance of the Frequency Table

            Statistics: Univariate Statistics

            Charts: Bar Charts, Pie Charts, and Histograms

Exercises

 

5. Computing Descriptive Statistics

Summarizing Data

            Scales of Measurement

            Mode, Median, and Arithmetic Average

            Comparing Mean and Median

Summarizing Time Spent Online

Measures of Variability

            Range

            Variance and Standard Deviation

            The Coefficient of Variation

Standard Scores

Summary

What’s Next?

How to Obtain Univariate Descriptive Statistics

            Options: Choosing Statistics and Sorting Variables

Exercises

 

6. Comparing Groups

Age, Education, and Internet Use

            Plotting Means

            Layers: Defining Subgroups by More than One Variable

Summary

What’s Next?

How to Obtain Subgroup Means

            Layers: Defining Subgroups by More than One Variable

            Options: Additional Statistics and Display of Labels

Exercises

 

7. Looking at Distributions

Marathon Completion Times

            Age and Gender

            Marathon Times for Mature Runners

Summary

What’s Next?

How to Explore Distributions

            Explore Statistics

            Graphical Displays

            Options

Exercises

 

8. Counting Responses for Combinations of Variables

Library Use and Education

            Row and Column Percentages

            Bar Charts

            Adding Control Variables

            Library Use and the Internet

Summary

What’s Next?

How to Obtain a Crosstabulation

            Layers: Three or More Variables at Once

            Cells: Percentages, Expected Counts, and Residuals

            Bivariate Statistics

            Format: Adjusting the Table Format

Exercises

 

9. Plotting Data

Examining Population Indicators

            Simple Scatterplots

            Scatterplot Matrices

            Overlay Plots

            Three-Dimensional Plots

            Identifying Unusual Points

            Rotating 3-D Scatterplots

Summary

What’s Next?

How to Obtain a Scatterplot

            Obtaining a Simple Scatterplot

            Obtaining an Overlay Scatterplot

            Obtaining a Scatterplot Matrix

            Obtaining a 3-D Scatterplot

            Editing a Scatterplot

Exercises

 

PART 3. TESTING HYPOTHESES

 

10. Evaluating Results from Samples

From Sample to Population

            A Computer Model

            The Effect of Sample Size

            The Binomial Test

Summary

What’s Next?

Exercises

 

11. The Normal Distribution

The Normal Distribution

            Samples from a Normal Distribution

            Means from a Normal Population

            Are the Sample Results Unlikely?

            Testing a Hypothesis

            Means from Non-Normal Distributions

            Means from a Uniform Distribution

Summary

What’s Next?

Exercises

 

12. Testing a Hypothesis about a Single Mean

Examining the Data

The T Distribution

            Calculating the T Statistic

Confidence Intervals

            Other Confidence Levels

            Confidence Interval for a Difference

            Confidence Intervals and Hypothesis Tests

Null Hypotheses and Alternative Hypotheses

            Rejecting the Null Hypothesis

Summary

What’s Next?

How to Obtain a One-Sample T Test

            Options: Confidence Level and Missing Data

Exercises

 

13. Testing a Hypothesis about Two Related Means

Marathon Runners in Paired Designs

            Looking at Differences

            Is the Mean Difference Zero?

            Two Approaches

The Paired-Samples T Test

            Are You Positive?

            Some Possible Problems

            Examining Normality

Summary

What’s Next?

How to Obtain a Paired-Samples T Test

            Options: Confidence Level and Missing Data

Exercises

 

14. Testing a Hypothesis about Two Independent

Means

Examining Television Viewing

            Distribution of Differences

            Standard Error of the Mean Difference

            Computing the T Statistic

            Output from the Two-Independent-Samples T Test

            Confidence Intervals for the Mean Difference

            Testing the Equality of Variances

Effect of Outliers

Introducing Education

            Can You Prove the Null Hypothesis?

            Interpreting the Observed Significance Level

            Power

            Monitoring Death Rates

            Does Significant Mean Important?

Summary

What’s Next?

How to Obtain an Independent-Samples T Test

            Define Groups: Specifying the Subgroups

            Options: Confidence Level and Missing Data

Exercises

 

15. One-Way Analysis of Variance

Hours in a Work Week

            Describing the Data

            Confidence Intervals for the Group Means

            Testing the Null Hypothesis

            Assumptions Needed for Analysis of Variance

            Analyzing the Variability

            Comparing the Two Estimates of Variability

            The Analysis-of-Variance Table

Multiple Comparison Procedures

            Television Viewing, Education, and Internet Use

Summary

What’s Next?

How to Obtain a One-Way Analysis of Variance

            Post Hoc Multiple Comparisons: Finding the Difference

            Options: Statistics and Missing Data

Exercises

 

16. Two-Way Analysis of Variance

The Design

            Examining the Data

            Testing Hypotheses

            Degree and Gender Interaction

            Necessary Assumptions

            Analysis-of-Variance Table

            Testing the Degree-by-Gender Interaction

            Testing the Main Effects

            Removing the Interaction Effect

            Where Are the Differences?

Multiple Comparison Results

            Checking Assumptions

A Look at Television

Extensions

Summary

What’s Next?

How to Obtain a GLM Univariate Analysis

            GLM Univariate: Model

            GLM Univariate: Plots

            GLM Univariate: Post Hoc

            GLM Univariate: Options

            GLM Univariate: Save

Exercises

 

17. Comparing Observed and Expected Counts

Freedom or Manners?

            Observed and Expected Counts

            The Chi-Square Statistic

            A Larger Table

Does College Open Doors?

A One-Sample Chi-Square Test

Power Concerns

Summary

What’s Next?

Exercises

 

18. Nonparametric Tests

Nonparametric Tests for Paired Data

            Sign Test

            Wilcoxon Test

            Whos Sending E-mail?

Mann-Whitney Test

Kruskal-Wallis Test

Friedman Test

Summary

How to Obtain Nonparametric Tests

            Chi-Square Test

            Binomial Test

            Two-Independent-Samples Tests

            Several-Independent-Samples Tests

            Two-Related-Samples Tests

            Several-Related-Samples Tests

            Options: Descriptive Statistics and Missing Values

Exercises

 

PART 4. EXAMINING RELATIONSHIPS

 

19. Measuring Association

Components of the Justice System

Proportional Reduction in Error

Measures of Association for Ordinal Variables

            Concordant and Discordant Pairs

            Measures Based on Concordant and Discordant Pairs

            Evaluating the Components

            Measuring Agreement

            Correlation-Based Measures

Measures Based on the Chi-Square Statistic

Summary

What’s Next?

Exercises

 

20. Linear Regression and Correlation

Life Expectancy and Birthrate

            Choosing the Best Line

Calculating the Least-Squares Line

            Calculating Predicted Values and Residuals

            Determining How Well the Line Fits

            Explaining Variability

            Some Warnings

Summary

What’s Next?

How to Obtain a Linear Regression

            Statistics: Further Information on the Model

            Residual Plots: Basic Residual Analysis

            Linear Regression Save: Creating New Variables

            Linear Regression Options

Exercises

 

21. Testing Regression Hypotheses

The Population Regression Line

            Assumptions Needed for Testing Hypotheses

Testing Hypotheses

            Testing that the Slope Is Zero

            Confidence Intervals for the Slope and Intercept

Predicting Life Expectancy

            Predicting Means and Individual Observations

            Standard Error of the Predicted Mean

            Confidence Intervals for the Predicted Means

            Prediction Intervals for Individual Cases

Summary

What’s Next?

How to Obtain a Bivariate Correlation

            Options: Additional Statistics and Missing Data

How to Obtain a Partial Correlation

            Options: Additional Statistics and Missing Data

Exercises

 

22. Analyzing Residuals

Residuals

            Standardized Residuals

            Studentized Residuals

            Checking for Normality

            Checking for Constant Variance

            Checking Linearity

Checking Independence

A Final Comment on Assumptions

Looking for Influential Points

            Studentized Deleted Residuals

Summary

What’s Next?

Exercises

 

23. Building Multiple Regression Models

Predicting Life Expectancy

            The Model

            Assumptions for Multiple Regression

            Examining the Variables

            Looking at How Well the Model Fits

            Examining the Coefficients

            Interpreting the Partial Regression Coefficients

            Changing the Model

            Partial Correlation Coefficients

            Tolerance and Multicollinearity

            Beta Coefficients

Building a Regression Model

            Methods for Selecting Variables

Summary

What’s Next?

How to Obtain a Multiple Linear Regression

            Options: Variable Selection Criteria

Exercises

 

24. Multiple Regression Diagnostics

Examining Normality

Scatterplots of Residuals

Leverage

Changes in the Coefficients

Cook’s Distance

Plots against Independent Variables

            Partial Regression Plot

Why Bother?

Summary

Exercises

 

Appendices

A. Obtaining Charts in PASW Statistics

Overview

Creating Bar Charts

            Creating a Chart Comparing Groups of Cases

            Data Summary Options

            Creating a Chart Comparing Several Variables

            Changing the Summary Statistic

            Options in Creating Charts

Modifying Charts

Modifying Chart Options

Hints on Editing Charts

Saving Chart Files

Line and Area Charts

Pie Charts

Boxplots

Case Labels

Error Bar Charts

Histograms

Normal Probability Plots

 

B. Transforming and Selecting Data

Data Transformations

            Transformations at a Glance

            Saving Changes

            Delaying Processing of Transformations

            Recoding Values

Computing Variables

            The Calculator Pad

            Automatic Recoding

            Conditional Transformations

Case Selection

            Temporary or Permanent Selection

            Other Selection Methods

 

C. The T Distribution

D. Areas under the Normal Curve

E. Descriptions of Data Files

F. Answers to Selected Exercises

 

Bibliography

Index

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