图书简介

1. Introduction to Statistical Thinking; 2. Garbage In, Garbage Out; Measurement Invalidity; Sampling Problems; Faulty Causal Inferences; Political Influences; Human Fallibility; 3. Issues in Data Preparation; Why Is Data Preparation Important?; Operationalization and Measurement; Nominal Measurement of Qualitative Variables; Measurement of Quantitative Variables; Issues in Levels of Measurement; Coding and Inputting Statistical Data; Available Computer Software for Basic Data Analysis; 4. Displaying Data in Tables and Graphic Forms; The Importance of Data Tables and Graphs; Types of Tabular and Visual Presentations; Tables and Graphs for Qualitative Variables; Tables and Graphs for Quantitative Variables; Ratios and Rates; Maps of Qualitative and Quantitative Variables; Hazards and Distortions in Visual Displays and Collapsing Categories; 5. Modes, Medians, Means, and More; Modes and Modal Categories; The Median and Other Measures of Location; The Mean and Its Meaning; Weighted Means; Strengths and Limitations of Mean Ratings; Choice of Measure of Central Tendency and Position; 6. Measures of Variation and Dispersion; The Range of Scores; The Variance and Standard Deviation; Variances and Standard Deviations for Binary Variables; Population versus Sample Variances & Standard Deviations; 7. The Normal Curve and Sampling Distributions; The Normal Curve; Z-Scores as Standard Scores; Reading a Normal Curve Table; Other Sampling Distributions; Binomial Distribution; t-Distribution; Chi-Square Distribution; F-Distribution; 8. Parameter Estimation and Confidence Intervals; Sampling Distributions and the Logic of Parameter Estimation; Inferences from Sampling Distributions to One Real Sample; Confidence Intervals: Large Samples, ? Known; Confidence Intervals for Population Means; Confidence Intervals for Population; Proportions; Confidence Intervals: Small Samples and Unknown ?; Properties of the t-Distribution; Confidence Intervals for Population Means for Unknown ?; Confidence Intervals for Population; Proportion for Unknown ?; 9. Introduction to Hypothesis Testing; Confidence Intervals Versus Hypothesis Testing; Basic Terminology and Symbols; Types of Hypotheses; Zone of Rejection and Critical Values; Significance Levels and Errors in Decision-Making; 10. Hypothesis Testing for Means and Proportions; Types of Hypothesis Testing; One-Sample Tests of the Population Mean; One-Sample Tests of a Population Proportion; Two Sample Test of Differences in Population Means; Two Sample Tests of Differences in Population Proportions; Issues in Testing Statistical Hypotheses; 11. Statistical Association in Contingency Tables; The Importance of Statistical Association and Contingency Tables; The Structure of a Contingency Table; Developing Tables of Total, Row, and Column Percentages; The Rules for Interpreting a Contingency Table; Specifying Causal Relations in Contingency Tables; Assessing the Magnitude of Bivariate; Associations in Contingency Tables; Visual and Intuitive Approach; The Chi-Square Test of Statistical Independence; Issues in Contingency Table Analysis; How Many Categories for Categorical Variables?; GIGO and the Value of Theory in Identifying Variables; Sample Size and Significance Tests; Other Measures of Association for Categorical Variables; 12. The Analysis of Variance (ANOVA); Overview of ANOVA and When it is Used; Partitioning Variation into Between and Within Group Differences; Calculating the Total Variation in a Dependent Variable; Calculating the Between-Group Variation; Calculating the Within-Group Variation; Hypothesis Testing and Measures of Association in ANOVA; Testing the Hypothesis of Equality of Group Means; Measures of Association in ANOVA; Issues in the Analysis of Variance; 13. Correlation and Regression; The Scatterplot of Two Interval/Ratio Variables; The Correlation Coefficient; Regression Analysis; The Computation of the Regression; Coefficient & Y-Intercept; Goodness of Fit of a Regression Equation; Hypothesis Testing and Tests of Statistical Significance; Using Regression Analysis for Predicting Outcomes; Issues in Bivariate Regression and Correlation Analysi; 14. Introduction to Multivariate Analysis; Why Do Multivariate Analysis?; Exploring Multiple Causes; Statistical Control; Types of Multivariate Analysis; Multivariate Contingency Table Analysis; Partial Correlation Coefficients; Multiple Regression Analysis $ https://global.oup.com/academic/product/9780195332544 $ Business & management; Social research & statistics; Social interaction

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