Preface |
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xi | |
I. Basic Concepts and Measures |
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Statistics in the Research Process |
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3 | (26) |
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Ideas into Research Projects |
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5 | (4) |
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Concepts into Propositions |
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9 | (2) |
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Variables into Hypotheses |
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11 | (3) |
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Observations into Records |
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14 | (2) |
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16 | (2) |
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18 | (4) |
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22 | (7) |
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29 | (40) |
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Frequency Distributions for Discrete and Continuous Variables |
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29 | (5) |
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Grouped and Cumulative Distributions |
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34 | (3) |
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Graphing Frequency Distributions |
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37 | (3) |
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Measures of Central Tendency |
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40 | (6) |
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46 | (7) |
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Percentiles and Quantiles |
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53 | (3) |
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Standardized Scores (Z Scores) |
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56 | (4) |
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Exploratory Data Analysis Methods for Displaying Continuous Data |
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60 | (9) |
II. Statistical Inference |
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Making Statistical Inferences |
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69 | (42) |
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Drawing Inferences About Populations from Samples |
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69 | (1) |
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Some Basic Probability Concepts |
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70 | (3) |
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Chebycheff's Inequality Theorem |
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73 | (2) |
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75 | (5) |
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The Central Limit Theorem |
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80 | (1) |
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Sample Point Estimates and Confidence Intervals |
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81 | (4) |
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85 | (3) |
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88 | (3) |
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Testing Hypotheses About Single Means |
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91 | (10) |
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101 | (1) |
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The Chi-Square and F Distributions |
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102 | (9) |
III. Analyzing Bivariate Relationships |
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111 | (28) |
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111 | (3) |
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ANOVA Tables: Sums of Squares, Mean Squares, F Ratio |
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114 | (7) |
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121 | (10) |
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The Correlation Ratio: Eta-Squared |
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131 | (1) |
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Testing Differences Among Means (Post Hoc) |
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132 | (7) |
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139 | (30) |
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Bivariate Crosstabulation |
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139 | (3) |
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Using Chi-Square to Test Significance |
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142 | (5) |
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Measuring Association: Q, Phi, Gamma, Tau c, Somers's dyx |
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147 | (12) |
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159 | (10) |
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Bivariate Regression and Correlation |
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169 | (38) |
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Scatterplots and Regression Lines |
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169 | (5) |
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Estimating a Linear Regression Equation |
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174 | (8) |
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182 | (5) |
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Significance Tests for Regression Parameters |
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187 | (7) |
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Standardizing Regression Coefficients |
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194 | (4) |
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Comparing Two Regression Equations |
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198 | (9) |
IV. Multivariate Models |
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The Logic of Multivariate Contingency Analysis |
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207 | (28) |
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Controlling Additional Variables |
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208 | (5) |
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Controlling for a Third Variable in 2 x 2 Tables |
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213 | (10) |
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The Partial Correlation Coefficient |
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223 | (12) |
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Multiple Regression Analysis |
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235 | (52) |
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An Example of a Three-Variable Regression Problem |
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236 | (4) |
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The Three-Variable Regression Model |
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240 | (15) |
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Multiple Regression with K Independent Variables |
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255 | (8) |
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Significance Tests for Parameters |
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263 | (7) |
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Comparing Nested Equations |
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270 | (1) |
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Dummy Variable Regression: ANCOVA with Interactions |
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271 | (7) |
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Comparisons Across Populations |
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278 | (9) |
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Nonlinear and Logistic Regression |
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287 | (40) |
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288 | (9) |
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Dichotomous Dependent Variables |
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297 | (2) |
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The Logistic Transformation and Its Properties |
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299 | (8) |
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Estimating and Testing Logistic Regression Equations |
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307 | (7) |
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The Multinomial-Logit Model |
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314 | (13) |
V. Advanced Topics |
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327 | (44) |
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Log-Linear Models for 2 x 2 Tables |
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328 | (9) |
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Log-Linear Models for Three-Variable Tables |
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337 | (12) |
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349 | (6) |
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Special Topics in Log-Linear Analysis |
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355 | (16) |
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Causal Models and Path Analysis |
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371 | (34) |
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371 | (3) |
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374 | (3) |
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377 | (28) |
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Structural Equation Models |
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405 | (68) |
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Review of Correlation and Covariance |
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406 | (2) |
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Reliability and Validity in Measurement Theory |
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408 | (6) |
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414 | (12) |
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Multiple-Indicator Causal Models |
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426 | (8) |
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Models with Ordered Indicators |
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434 | (15) |
Appendices |
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449 | (8) |
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B. Critical Values of Chi Square (table) |
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457 | (2) |
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C. Areas Under the Normal Curve (table) |
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459 | (6) |
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D. Student's t Distribution (table) |
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465 | (2) |
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E. F Distribution (table) |
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467 | (4) |
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F. Fisher's r-to-Z Transformation (table) |
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471 | (2) |
Glossary of Terms |
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473 | (14) |
List of Mathematical and Statistical Symbols |
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487 | (8) |
Answers to Problems |
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495 | (28) |
Index |
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523 | |