TY  - BOOK
AU  - Walsh,Anthony
AU  - Ollenburger,Jane C.
TI  - Essential statistics for the social and behavioral sciences: a conceptual approach 
SN  - 0130193399
AV  - HA29. W33573 2001
U1  - 300.727 
PY  - 2001///
CY  - Upper Saddle River, NJ
PB  - Prentice Hall
KW  - Social sciences
KW  - Statistical methods
N1  - Includes bibliographical references and index; Preface --; Chapter 1; Introduction to Statistical Analysis --; Why Study Statistics? --; Thinking Statistically --; Descriptive and Inferential Statistics --; Descriptive Statistics --; Inferential Statistics --; Statistics and Error --; Parametric and Nonparametric Statistics --; Operationalization --; Reliability and Validity --; Measurement --; Dependent and Independent Variables --; Nominal Level --; Ordinal Level --; Interval Level --; Ratio Level --; The Role of Statistics in Science --; Summary --; Practice Application: Variables and Levels of Measurement --; Problems --; Chapter 2; Presenting and Summarizing Data --; Types of Frequency Distributions --; Interpreting Cumulative Frequencies --; Frequency Distribution of Grouped Data --; Limits, Sizes, and Midpoints of Class Intervals --; Advantages and Disadvantages of Grouping Data --; Bar Graphs and Pie Charts --; Histograms and Frequency Polygons --; Numerical Summation of Data: Percentages, Proportions, and Ratios --; Summary --; Practice Application: Displaying and Summarizing Data --; Problems --; Chapter 3; Central Tendency and Dispersion --; Measures of Central Tendency --; Mode --; Median --; Computing the Median with Grouped Data --; The Mean --; Computing the Mean from Grouped Data --; A Research Example --; Choosing a Measure of Central Tendency --; Measures of Dispersion --; Range --; Standard Deviation --; Computational Formula for s --; Variability and Variance --; Computing the Standard Deviation from Grouped Data --; Coefficient of Variation --; Index of Qualitative Variation --; Summary --; Practice Application: Central Tendency and Dispersion --; Reference --; Problems --; Chapter 4; Probability and the Normal Curve --; Probability --; The Multiplication Rule --; The Addition Rule --; Theoretical Probability Distributions --; The Normal Curve --; Different Kinds of Curves --; The Standard Normal Curve --; The z Scores --; Finding Area of the Curve Below the Mean --; Summary --; Practice Application: The Normal Curve and z Scores --; Reference --; Problems --; Chapter 5; The Sampling Distribution and Estimation Procedures --; Sampling --; Simple Random Sampling --; Stratified Random Sampling --; The Sampling Distribution --; The Central Limit Theorem --; Standard Error of the Sampling Distribution --; Point and Interval Estimates --; Confidence Intervals and Alpha Levels --; Calculating Confidence Intervals --; Sampling and Confidence Intervals --; Interval Estimates for Proportions --; Estimating Sample Size --; Estimating Sample Size for Proportions --; Summary --; Practice Application: The Sampling Distribution and Estimation --; Problems --; Chapter 6; Hypothesis Testing: Interval/Ratio Data --; The Logic of Hypothesis Testing --; The Evidence and Statistical Significance --; Errors in Hypothesis Testing --; One Sample z Test --; Decision Rule --; The t Test --; Degrees of Freedom --; The t Distribution --; Directional Hypotheses: One- and Two-Tailed Tests --; Computing t --; t Test for Correlated (Dependent) Means --; Effects of Sample Variance on H[subscript 0] Decision --; Large Sample t Test: A Computer Example --; Interpreting the Printout --; Calculating t with Unequal Variances --; Testing Hypotheses for Single-Sample Proportions --; Statistical Versus Substantive Significance, and Strength of Association --; Summary --; Practice Application: t Test --; Problems --; Chapter 7; Analysis of Variance --; Assumptions of Analysis of Variance --; The Basic Logic of ANOVA --; The Idea of Variance Revisited --; The Advantage of ANOVA over Multiple Tests --; The F Distribution --; An Example of ANOVA --; Determining Statistical Significance: Mean Square and the F Ratio --; ETA Squared --; Multiple Comparisons: The Scheffe Test --; Two-Way Analysis of Variance --; Determining Statistical Significance --; Significance Levels --; Understanding Interaction --; A Research Example of a Significant Interaction Effect --; Summary --; Practice Application --; Problems --; Chapter 8; Hypothesis Testing with Categorical Data: Chi-Square Test --; Table Construction --; Putting Percentages in Tables --; Assumptions for the Use of Chi-Square --; The Chi-Square Distribution --; Yates' Correction for Continuity --; Chi-Square Distribution and Goodness of Fit --; Chi-Square-Based Measures of Association --; Sample Size and Chi-Square --; Contingency Coefficient --; Cramer's V --; A Computer Example of Chi-Square --; Kruskal-Wallis One-Way Analysis of Variance --; Summary --; Practice Application: Chi-Square --; Reference --; Problems --; Chapter 9; Nonparametric Measures of Association --; The Idea of Association --; Does an Association Exist? --; What Is the Strength of the Association? --; What Is the Direction of the Association? --; Proportional Reduction in Error --; The Concept of Paired Cases --; A Computer Example --; Gamma --; Lambda --; Somer's d --; Tau-B --; The Odd's Ratio and Yule's Q --; Spearman's Rank Order Correlation --; Which Test of Association Should We Use? --; Summary --; Practice Application: Nonparametric Measures of Association --; Reference --; Problems --; Chapter 10; Elaboration of Tabular Data --; Causal Analysis --; Criteria for Causality --; Association --; Temporal Order --; Spuriousness --; Necessary Cause --; Sufficient Cause --; Necessary and Sufficient Cause --; A Statistical Demonstration of Cause-and-Effect Relationships --; Multivariate Contingency Analysis --; Introducing a Third Variable --; Explanation and Interpretation --; Illustrating Elaboration Outcomes --; Controlling for One Variable --; Further Elaboration: Two Control Variables --; Partial Gamma --; When Not to Compute Partial Gamma --; Problems with Tabular Elaboration --; Summary --; Practice Application: Bivariate Elaboration --; Reference --; Problems --; Chapter 11; Bivariate Correlation and Regression --; Preliminary Investigation: The Scattergram --; The Slope --; The Intercept --; The Pearson Correlation Coefficient --; Covariance and Correlation --; Partitioning r Squared and Sum of Squares --; Standard Error of the Estimate --; Standard Error of r --; Significance Testing for Pearson's r --; The Interrelationship of b, r, and [beta] --; Summarizing Properties of r, b, and [beta] --; Summarizing Prediction Formulas --; A Computer Example of Bivariate Correlation and Regression --; Practice Application: Bivariate Correlation and Regression --; Practice Application: Bivariate Correlation and Regression --; Reference --; Problems --; Chapter 12; Multivariate Correlation and Regression --; Partial Correlation --; Computing Partial Correlations --; Computer Example and Interpretation --; Second-Order Partials: Controlling for Two Independent Variables --; The Multiple Correlation Coefficient --; Multiple Regression --; The Unstandardized Partial Slope --; The Standardized Slope ([beta]) --; A Computer Example of Multiple Regression and Interpretation --; Summary Statistics: Multiple R, R[superscript 2], s[subscript Y.X], and ANOVA --; The Predictor Variables: b, [beta], and t --; A Visual Representation of Multiple Regression --; Dummy Variable Regression --; Regression and Interaction --; Summary --; Practice Application: Partial Correlation --; Problems --; Chapter 13; Introduction to Logistic Regression --; An Example of Logit Regression --; Interpretation: Probabilities and Odds --; Assessing the Model Fit --; Multiple Logistic Regression --; Summary --; Practice Application: Logistic Regression --; Problem --; Appendix A; Statistical Tables --; Appendix B; Answers to Odd Numbered Problems --; Chapter 1 --; Chapter 2 --; Chapter 3 --; Chapter 4 --; Chapter 5 --; Chapter 6 --; Chapter 7 --; Chapter 8 --; Chapter 9 --; Chapter 10 --; Chapter 11 --; Chapter 12 --; Chapter 13 --; Glossary --; Index
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