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The Essentials of Statistics: A Tool for Social Research,9780495009757
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The Essentials of Statistics: A Tool for Social Research

by
Edition:
1st
ISBN13:

9780495009757

ISBN10:
049500975X
Format:
Paperback
Pub. Date:
8/1/2006
Publisher(s):
Wadsworth Publishing

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Summary

Prologue: Basic Review of Mathematics. 1. Introduction. PART I. Descriptive Statistics. 2. Basic Descriptive Statistics: Percentages, Ratios and Rates, Tables, Charts, and Graphs. 3. Measures of Central Tendency. 4. Measures of Dispersion. 5. The Normal Curve. PART II. Inferential Statistics. 6. Inferential Statistics, the Sampling Distribution and Estimation. 7. Hypothesis Testing I: The One Sample Case. 8. Hypothesis Testing II: The Two Sample Case. 9. Hypothesis Testing III: The Analysis of Variance. 10. Hypothesis Testing IV: Chi Square. PART III. Measures of Association. 11. Bivariate Association For Variables Measured at the Nominal Level. 12. Bivariate Association For Variables Measured at the Ordinal Level. 13. Association Between Variables Measured at the Interval-Ratio Level. PART IV. Multivariate Techniques. 14. Partial Correlation and Multiple Regression and Correlation. Appendix A. Area under the Normal Curve. Appendix B. Distribution of t. Appendix C. Distribution of Chi Square. Appendix D. Distribution of F. Appendix E. Using Statistics: Ideas for Research Projects. Appendix F. An Introduction to Computerized Statistics Programs (SPSS for Windows). Appendix G. Code Book for the General Social Survey, 2004. Answers to Odd-Numbered Computational Problems. Glossary. Index.

Table of Contents

Preface xv
Prologue / Basic Mathematics Review 1(7)
Introduction
8(19)
Why Study Statistics?
8(1)
The Role of Statistics in Scientific Inquiry
9(3)
The Goals of This Text
12(1)
Descriptive and Inferential Statistics
13(3)
Statistics in Everyday Life: Introduction
15(1)
Level of Measurement
16(11)
Step by Step: Determining the Level of Measurement of a Variable
19(2)
Summary
21(1)
Glossary
22(1)
Problems
22(3)
Introduction to SPSS and the General Social Survey
25(2)
PART I DESCRIPTIVE STATISTICS
27(96)
Basic Descriptive Statistics: Percentages, Ratios and Rates, Tables, Charts, and Graphs
28(37)
Percentages and Proportions
28(3)
Application 2.1
30(1)
Step by Step: Computing Percentages and Proportions
31(1)
Ratios, Rates, and Percentage Change
31(5)
Application 2.2
33(1)
Application 2.3
33(1)
Application 2.4
34(1)
Statistics in Everyday Life: Road Rage
35(1)
Step by Step: Computing Ratios, Rates, and Percent Change
36(1)
Frequency Distributions: Introduction
36(1)
Frequency Distributions for Variables Measured at the Nominal and Ordinal Levels
37(2)
Frequency Distributions for Variables Measured at the Interval-Ratio Level
39(7)
Step by Step: Computing Midpoints
42(3)
Step by Step: Constructing Frequency Distributions for Interval-Ratio Variables
45(1)
Constructing Frequency Distributions for Interval-Ratio-Level Variables: A Review
46(1)
Application 2.5
47(1)
Charts and Graphs
47(18)
Statistics in Everyday Life: Increasing Congestion and Lost Time on the Road
52(1)
Summary
53(1)
Summary of Formulas
53(1)
Glossary
53(1)
Multimedia Resources
54(1)
Problems
54(5)
Using SPSS for Windows to Produce Frequency Distributions and Graphs
59(6)
Measures of Central Tendency
65(20)
Introduction
65(1)
The Mode
65(2)
The Median
67(2)
Step by Step: Computing the Median
69(1)
The Mean
69(1)
Application 3.1
70(1)
Some Characteristics of the Mean
70(4)
Step by Step: Computing the Mean
71(3)
Statistics in Everyday Life: Housing Costs, Football Salaries, and Skew
74(1)
Choosing a Measure of Central Tendency
74(11)
Summary
76(1)
Summary of Formulas
77(1)
Glossary
77(1)
Multimedia Resources
77(1)
Problems
77(5)
Using SPSS for Windows for Measures of Central Tendency
82(3)
Measures of Dispersion
85(18)
Introduction
85(1)
The Range (R) and Interquartile Range (Q)
86(1)
Computing the Range and Interquartile Range
87(1)
The Standard Deviation and Variance
88(5)
Step by Step: Computing the Standard Deviation
91(1)
Application 4.1
91(1)
Application 4.2
92(1)
Computing the Standard Deviation: An Additional Example
93(1)
Statistics in Everyday Life: Where's the Nicest Place to Live?
94(1)
Interpreting the Standard Deviation
94(9)
Summary
95(1)
Summary of Formulas
96(1)
Glossary
96(1)
Multimedia Resources
96(1)
Problems
96(3)
Using SPSS for Windows for Measures of Dispersion
99(4)
The Normal Curve
103(20)
Introduction
103(3)
Statistics in Everyday Life: How Normal Is the Normal Curve?
106(1)
Computing Z Scores
106(1)
Step by Step: Computing Z Scores
107(1)
The Normal Curve Table
107(2)
Finding Total Area Above and Below a Score
109(2)
Finding Areas Between Two Scores
111(3)
Step by Step: Finding Areas Above and Below Positive and Negative Z Scores
111(1)
Application 5.1
112(1)
Step by Step: Finding Areas Between Z Scores
113(1)
Application 5.2
114(1)
Using the Normal Curve to Estimate Probabilities
114(9)
Step by Step: Finding Probabilities
117(1)
Application 5.3
117(1)
Statistics in Everyday Life: Applying the Laws of Probability
118(1)
Summary
119(1)
Summary of Formulas
119(1)
Glossary
119(1)
Multimedia Resources
119(1)
Problems
120(3)
PART II INFERENTIAL STATISTICS
123(128)
Introduction to Inferential Statistics, the Sampling Distribution, and Estimation
124(28)
Introduction
124(1)
Probability Sampling
125(1)
The Sampling Distribution
126(4)
The Sampling Distribution: An Additional Example
130(2)
Symbols and Terminology
132(1)
Introduction to Estimation
133(1)
Bias and Efficiency
133(3)
Estimation Procedures: Introduction
136(2)
Interval Estimation Procedures for Sample Means (Large Samples)
138(2)
Step by Step: Constructing Confidence Intervals for Sample Means
140(1)
Interval Estimation Procedures for Sample Proportions (Large Samples)
140(3)
Application 6.1
141(1)
Step by Step: Constructing Confidence Intervals for Sample Proportions
142(1)
Application 6.2
143(1)
A Summary of the Computation of Confidence Intervals
143(1)
Statistics in Everyday Life: Election Projections, Polls, and Surveys
144(1)
Controlling the Width of Interval Estimates
144(8)
Summary
148(1)
Summary of Formulas
148(1)
Glossary
148(1)
Multimedia Resources
149(1)
Problems
149(3)
Hypothesis Testing I: The One-Sample Case
152(30)
Introduction
152(1)
An Overview of Hypothesis Testing
153(5)
The Five-Step Model for Hypothesis Testing
158(3)
Step by Step: Testing the Significance of the Difference Between a Sample Mean and a Population Mean (Large Samples): Computing Z(obtained) and Interpreting Results
161(1)
One-Tailed and Two-Tailed Tests of Hypothesis
161(6)
Application 7.1
162(5)
Selecting an Alpha Level
167(1)
The Student's t Distribution
168(5)
Step by Step: Testing the Significance of the Difference Between a Sample Mean and a Population Mean (Small Samples): Computing t(obtained) and Interpreting Results
172(1)
Tests of Hypotheses for Single-Sample Proportions (Large Samples)
173(9)
Step by Step: Testing the Significance of the Difference Between a Sample Proportion and a Population Proportion (Large Samples): Computing Z(obtained) and Interpreting Results
175(1)
Application 7.2
175(1)
Summary
176(1)
Summary of Formulas
177(1)
Glossary
177(1)
Multimedia Resources
178(1)
Problems
178(4)
Hypothesis Testing II: The Two-Sample Case
182(25)
Introduction
182(1)
Hypothesis Testing with Sample Means (Large Samples)
182(8)
Step by Step: Testing the Difference in Sample Means for Significance (Large Samples): Computing Z(obtained) and Interpreting Results
186(1)
Application 8.1
187(1)
Statistics in Everyday Life: Culture Wars
187(3)
Hypothesis Testing with Sample Means (Small Samples)
190(2)
Step by Step: Testing the Difference in Sample Means for Significance (Small Samples): Computing t(obtained) and Interpreting Results
192(1)
Hypothesis Testing with Sample Proportions (Large Samples)
192(2)
The Limitations of Hypothesis Testing: Significance Versus Importance
194(13)
Step by Step: Testing the Difference in Sample Proportions for Significance (Large Samples): Computing Z(obtained) and Interpreting Results
195(1)
Application 8.2
196(1)
Summary
197(1)
Summary of Formulas
198(1)
Glossary
198(1)
Multimedia Resources
199(1)
Problems
199(4)
Using SPSS for Windows to Test The Significance of the Difference Between Two Means
203(4)
Hypothesis Testing III: The Analysis of Variance
207(21)
Introduction
207(1)
The Logic of the Analysis of Variance
208(1)
The Computation of ANOVA
209(2)
A Computational Shortcut
211(1)
Step by Step: Computing ANOVA
211(1)
A Computational Example
212(1)
A Test of Significance for ANOVA
212(3)
Application 9.1
214(1)
An Additional Example for Computing and Testing the Analysis of Variance
215(3)
Statistics in Everyday Life: Who Gets Rich?
217(1)
The Limitations of the Test
218(10)
Summary
219(1)
Summary of Formulas
220(1)
Glossary
220(1)
Multimedia Resources
221(1)
Problems
221(3)
Using SPSS for Windows to Conduct Analysis of Variance
224(4)
Hypothesis Testing IV: Chi Square
228(23)
Introduction
228(1)
Bivariate Tables
229(1)
The Logic of Chi Square
230(1)
The Computation of Chi Square
231(2)
Step by Step: Computing Chi Square
233(1)
The Chi Square Test for Independence
233(3)
Step by Step: Computing Column Percents
236(1)
The Chi Square Test: An Additional Example
236(4)
Application 10.1
237(3)
The Limitations of the Chi Square Test
240(11)
Summary
241(1)
Summary of Formulas
241(1)
Glossary
242(1)
Multimedia Resources
242(1)
Problems
242(4)
Using SPSS for Windows to Conduct the Chi Square Test
246(5)
PART III BIVARIATE MEASURES OF ASSOCIATION
251(78)
Introduction to Bivariate Association and Measures of Association for Variables Measured at the Nominal Level
252(27)
Statistical Significance and Theoretical Importance
252(1)
Association Between Variables and Bivariate Tables
253(2)
Three Characteristics of Bivariate Associations
255(4)
Introduction to Measures of Association
259(1)
Application 11.1
260(1)
Measures of Association for Variables Measured at the Nominal Level: Chi Square-Based Measures
260(4)
Step by Step: Calculating and Interpreting Phi and Cramer's V
263(1)
Application 11.2
264(1)
Lambda: A Proportional Reduction in Error Measure of Association for Nominal-Level Variables
264(15)
Step by Step: Calculating and Interpreting Lambda
268(1)
Statistics in Everyday Life: The Truth About Astrology
269(1)
Summary
270(1)
Summary of Formulas
270(1)
Glossary
270(1)
Multimedia Resources
271(1)
Problems
271(3)
Using SPSS for Windows to Test Bivariate Association for Significance and Association
274(5)
Association Between Variables Measured at the Ordinal Level
279(23)
Introduction
279(1)
Proportional Reduction in Error (PRE)
279(1)
Gamma
280(4)
Determining the Direction of Relationships
284(4)
Step by Step: Computing and Interpreting Gamma
287(1)
Application 12.1
288(1)
Spearman's Rho (rs)
288(14)
Step by Step: Computing and Interpreting Spearman's Rho
291(1)
Application 12.2
292(1)
Summary
292(1)
Summary of Formulas
293(1)
Glossary
293(1)
Multimedia Resources
293(1)
Problems
293(5)
Using SPSS for Windows to Produce Ordinal-Level Measures of Association
298(4)
Association Between Variables Measured at the Interval-Ratio Level
302(27)
Introduction
302(1)
Scattergrams
302(4)
Regression and Prediction
306(2)
The Computation of a and b
308(3)
Step by Step: Computing the Slope (b)
310(1)
Step by Step: Computing the Y Intercept (a)
311(1)
The Correlation Coefficient (Pearson's r)
311(2)
Step by Step: Computing Pearson's r
312(1)
Interpreting the Correlation Coefficient: r2
313(4)
Application 13.1
316(1)
The Correlation Matrix
317(12)
Statistics in Everyday Life: Correlation, Causation, and Cancer
319(1)
Summary
320(1)
Summary of Formulas
321(1)
Glossary
321(1)
Multimedia Resources
322(1)
Problems
322(3)
Using SPSS for Windows to Produce Pearson's r
325(4)
PART IV MULTIVARIATE TECHNIQUES
329(26)
Partial Correlation and Multiple Regression and Correlation
330(25)
Introduction
330(1)
Partial Correlation
330(5)
Step by Step: Computing and Interpreting Partial Correlations
334(1)
Multiple Regression: Predicting the Dependent Variable
335(3)
Step by Step: Computing the Regression Coefficients (b and a)
338(1)
Multiple Regression: Assessing the Effects of the Independent Variables
338(3)
Step by Step: Computing Beta-Weight (b*)
340(1)
Multiple Correlation
341(1)
Step by Step: Computing R2
342(1)
The Limitations of Multiple Regression and Correlation
342(13)
Application 14.1
343(2)
Statistics in Everyday Life: Beta-Weights and Baseball
345(1)
Summary
346(1)
Summary of Formulas
346(1)
Glossary
347(1)
Multimedia Resources
347(1)
Problems
348(3)
Using SPSS for Windows for Regression Analysis
351(4)
Appendix A Area Under the Normal Curve 355(4)
Appendix B Distribution of t 359(1)
Appendix C Distribution of Chi Square 360(1)
Appendix D Distribution of F 361(2)
Appendix E Using Statistics: Ideas for Research Projects 363(5)
Appendix F An Introduction to SPSS for Windows 368(9)
Appendix G Codebook for the General Social Survey, 2004 377(8)
Appendix H Glossary of Symbols 385(2)
Answers to Odd-Numbered Computational Problems 387(8)
Glossary 395(5)
Index 400


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