# Introduction to statistics for the social sciences

Primis Custom Pub., New York, ©1998
277 pages : illustrations ; 24 cm + 2 computer discs
9780072909852, 0072909854
41429100
Forward
 Introduction to Statistics
1(11)
 Why Should I Care About Statistics?
1(1)
2(1)
 So, What Exactly Are Statistics?
3(1)
 How Difficult Will This Be If I'm Not a Mathematical Genius?
4(1)
 Summary
4(1)
 Key Terms
4(1)
 Problems
4(1)
 Notes
5(5)
 Computer Section
10(2)
 Collecting and Measuring Data
12(31)
 Collecting Data
12(1)
 Research Methods
12(4)
 Levels of Measurement
16(4)
 Summary
20(1)
 Key Terms
21(1)
 Problems
21(1)
 Notes
22(1)
 Computer Section
23(20)
 Describing Data
43(22)
 Describing Data
43(1)
 Distributions of Data
43(1)
 Graphing Distributions
44(3)
 Shapes of Distributions
47(1)
 Measures of Central Tendency
48(6)
 Measures of Dispersion
54(4)
 Summary
58(1)
 Key Terms
58(1)
 Problems
59(2)
 Notes
61(1)
 Computer Section
62(3)
 Working with Distributions
65(19)
 Types of Normal Distributions
65(1)
 Sample Distribution
65(5)
 Population Distribution
70(1)
 Sampling Distribution
71(2)
 Distribution of Differences
73(4)
 Summary
77(1)
 Key Terms
77(1)
 Problems
77(3)
 Notes
80(1)
 Computer Section
81(3)
 Hypothesis Testing and the z-test
84(20)
 Introduction to Inferential Statistics
84(1)
 What is a Hypothesis?
84(2)
 Null and Alternative Hypotheses
86(3)
 Probability and Hypothesis Testing
89(2)
 The One-Sample z-Test
91(6)
 The Two-Sample z-Test
97(1)
 Summary
98(1)
 Key Terms
99(1)
 Problems
99(3)
 Notes
102(1)
 Computer Section
103(1)
 The t-test
104(21)
 From z to t
104(1)
 The t-distributions
105(2)
 Critical Values and the t-distribution
107(2)
 Degrees of Freedom, Critical Values, and the t-Table
109(1)
 An Example of the t-test
110(3)
 t-test Flowchart
113(1)
 Summary
113(1)
 Key Terms
113(1)
 Problems
113(5)
 Notes
118(4)
 Computer Section
122(3)
 Single-Factor Analysis of Variance (ANOVA)
125(24)
 From t to F
125(2)
 Overview of Single-Factor Analysis of Variance
127(4)
 Degrees of Freedom
131(2)
 Calculating the F-Statistic
133(1)
 Critical Values and the F-table
134(1)
 An Anova (F-Test) Example
135(3)
 ANOVA Formula Summary
138(1)
 Summary
139(1)
 Key Terms
139(1)
 Problems
139(3)
 Notes
142(4)
 Computer Section
146(3)
 Multiple-Factor Analysis of Variance
149(28)
 Introduction to Multiple-Factor ANOVA
149(1)
 Factorial Designs
149(3)
 Main and Interaction Effects
152(4)
 Conducting a Multiple Factor Analysis of Variance
156(5)
 An Example of Multiple-Factor ANOVA
161(3)
 Summary
164(1)
 Key Terms
165(1)
 Problems
165(8)
 Computer Section
173(4)
 Correlation
177(18)
 What is Simple Correlation?
177(2)
 Computing a Simple Correlation: the Pearson r
179(3)
 Testing a Correlation for Statistical Significance
182(3)
 Correlation Does Not Equal Causation
185(1)
 Amount of Variance Explained
185(1)
 An Example of Correlation
186(1)
 Summary
187(1)
 Key Terms
188(1)
 Problems
188(2)
 Notes
190(3)
 Computer Section
193(2)
 Linear Regression
195(15)
 From Correlation to Regression
195(1)
 Deriving the Regression Equation
196(1)
 Prediction and Error
197(2)
 Significance of the Regression Equation
199(5)
 An Example of Bivariate Linear Regression
204(1)
 Summary
205(1)
 Key Terms
205(1)
 Problems
205(1)
 Notes
206(1)
 Computer Section
207(3)
 Multiple Regression
210(26)
 Beyond Simple Correlation and Bivariate Linear Regression
210(3)
 Multiple Regression
213(1)
 Testing the Significance of a Multiple Regression Equation
214(2)
 Types of Multiple Regression
216(4)
 An Example of Multiple Regression
220(2)
 Summary
222(1)
 Key Terms
223(1)
 Problems
223(3)
 Notes
226(5)
 Computer Section
231(5)
 Chi-Square Analysis
236(21)
 Parametric vs. Nonparametric Tests
236(1)
 The Chi-Square Test
236(2)
 Chi-Square Goodness-of-Fit Test (One Sample)
238(1)
 Chi-Square Test of Association (Multiple Samples)
239(2)
 Beyond the Chi-Square Test
241(2)
 An Example of Chi-Square Analysis
243(2)
 Summary
245(1)
 Key Terms
245(1)
 Problems
246(3)
 Note
249(3)
 Computer Section
252(5)
Appendices257(1)
 Appendix A: Tables
257(7)