Schuyler W. Huck is Distinguished Professor and Chancellor's Teaching Scholar at the University of Tennessee - Knoxville. A prolific author on improving statistical instruction and helping consumers decipher research reports, his publications have been cited in over 337 journals.
Inhaltsangabe
Introduction to the Classic Edition. Part 1. Descriptive Statistics. 1.1. Measures of Central Tendency. 1.2. The Mean of Means. 1.3. The Mode s Location. 1.4. The Standard Deviation. Part 2. Distributional Shape. 2.1. The Shape of the Normal Curve. 2.2. Skewed Distributions and Measures of Central Tendency. 2.3. Standard Scores and Normality. 2.4. Rectangular Distributions and Kurtosis. Part 3. Bivariate Correlation. 3.1. Correlation Coefficients. 3.2. Correlation and Causality. 3.3. The Effect of a Single Outlier on Pearson s r. 3.4. Relationship Strength and r. 3.5. The Meaning of r = 0. Part 4. Reliability and Validity. 4.1. Statistical Indices of Reliability and Validity. 4.2. Interrater Reliability. 4.3. Cronbach s Alpha and Unidimensionality. 4.4. Range Restriction and Predictive Validity. Part 5. Probability. 5.1. The Binomial Distribution and N. 5.2. A Random Walk With a Perfectly Fair Coin. 5.3. Two Goats and a Car. 5.4. Identical Birthdays. 5.5. The Sum of an Infinite Number of Numbers. 5.6.Being Diagnosed With a Rare Disease. 5.7. Risk Ratios and Odds Ratios. Part 6. Sampling. 6.1.The Character of Random Samples. 6.2. Random Replacements When Sampling. 6.3 Precision and the Sampling Fraction. 6.4. Matched Samples. 6.5. Finite Versus Infinite Populations. Part 7. Estimation. 7.1. Interpreting a Confidence Interval. 7.2. Overlapping Confidence Intervals. 7.3. The Mean ± the Standard Error. 7.4. Confidence Intervals and Replication. Part 8. Hypothesis Testing. 8.1. Alpha and Type I Error Risk. 8.2. The Null Hypothesis. 8.3.Disproving Ho. 8.4. The Meaning of p. 8.5. Directionality and Tails. 8.6. The Relationship Between Alpha and Beta Errors. Part 9. t-Tests Involving One or Two Means. 9.1.Correlated t-Tests. 9.2. The Difference Between Two Means If p < .00001. 9.3. The Robustness of a t-Test When n1 = n2. Part 10. ANOVA and ANCOVA. 10.1. Pairwise Comparisons. 10.2. The Cause of a Significant Interaction. 10.3. Equal Covariate Means in ANCOVA. Part 11. Practical Significance, Power, and Effect Size. 11.1. Statistical Significance Versus Practical Significance. 11.2. A Priori and Post Hoc Power. 11.3. Eta Squared and Partial Eta Squared. Part 12. Regression. 12.1. Comparing Two rs; Comparing Two bs. 12.2. R2. 12.3. Predictor Variables that Are Uncorrelated with Y. 12.4. Beta Weights.
Introduction to the Classic Edition. Part 1. Descriptive Statistics. 1.1. Measures of Central Tendency. 1.2. The Mean of Means. 1.3. The Mode s Location. 1.4. The Standard Deviation. Part 2. Distributional Shape. 2.1. The Shape of the Normal Curve. 2.2. Skewed Distributions and Measures of Central Tendency. 2.3. Standard Scores and Normality. 2.4. Rectangular Distributions and Kurtosis. Part 3. Bivariate Correlation. 3.1. Correlation Coefficients. 3.2. Correlation and Causality. 3.3. The Effect of a Single Outlier on Pearson s r. 3.4. Relationship Strength and r. 3.5. The Meaning of r = 0. Part 4. Reliability and Validity. 4.1. Statistical Indices of Reliability and Validity. 4.2. Interrater Reliability. 4.3. Cronbach s Alpha and Unidimensionality. 4.4. Range Restriction and Predictive Validity. Part 5. Probability. 5.1. The Binomial Distribution and N. 5.2. A Random Walk With a Perfectly Fair Coin. 5.3. Two Goats and a Car. 5.4. Identical Birthdays. 5.5. The Sum of an Infinite Number of Numbers. 5.6.Being Diagnosed With a Rare Disease. 5.7. Risk Ratios and Odds Ratios. Part 6. Sampling. 6.1.The Character of Random Samples. 6.2. Random Replacements When Sampling. 6.3 Precision and the Sampling Fraction. 6.4. Matched Samples. 6.5. Finite Versus Infinite Populations. Part 7. Estimation. 7.1. Interpreting a Confidence Interval. 7.2. Overlapping Confidence Intervals. 7.3. The Mean ± the Standard Error. 7.4. Confidence Intervals and Replication. Part 8. Hypothesis Testing. 8.1. Alpha and Type I Error Risk. 8.2. The Null Hypothesis. 8.3.Disproving Ho. 8.4. The Meaning of p. 8.5. Directionality and Tails. 8.6. The Relationship Between Alpha and Beta Errors. Part 9. t-Tests Involving One or Two Means. 9.1.Correlated t-Tests. 9.2. The Difference Between Two Means If p < .00001. 9.3. The Robustness of a t-Test When n1 = n2. Part 10. ANOVA and ANCOVA. 10.1. Pairwise Comparisons. 10.2. The Cause of a Significant Interaction. 10.3. Equal Covariate Means in ANCOVA. Part 11. Practical Significance, Power, and Effect Size. 11.1. Statistical Significance Versus Practical Significance. 11.2. A Priori and Post Hoc Power. 11.3. Eta Squared and Partial Eta Squared. Part 12. Regression. 12.1. Comparing Two rs; Comparing Two bs. 12.2. R2. 12.3. Predictor Variables that Are Uncorrelated with Y. 12.4. Beta Weights.
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