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Table of Contents

1. Statistics, Data, and Statistical Thinking.

The Science of Statistics. Types of Statistical Applications. Fundamental Elements of Statistics. Types of Data. Collecting Data. The Role of Statistics in Critical Thinking.

2. Methods for Describing Sets of Data.

Describing Qualitative Data. Graphical Methods for Describing Quantitative Data. Summation Notation. Numerical Measures of Central Tendency. Numerical Measures of Variability. Interpreting the Standard Deviation. Numerical Measures of Relative Standing. Methods for Detecting Outliers (Optional). Graphing Bivariate Relationships (Optional). Distorting the Truth with Descriptive Techniques.

3. Probability.

Events, Sample Spaces, and Probability. Unions and Intersections. Complementary Events. The Additive Rule and Mutually Exclusive Events. Conditional Probability. The Multiplicative Rule and Independent Events. Random Sampling.

4. Random Variables and Probability Distribution.

Two Types of Random Variables. Probability Distributions for Discrete Random Variables. The Binomial Random Variable. Continuous Probability Distributions. The Normal Distribution. Descriptive Methods for Assessing Normality. Approximating a Binomial Distribution with a Normal Distribution (Optional). Sampling Distributions. The Central Limit Theorem.

5. Inferences Based on a Single Sample: Estimation with Confidence Intervals.

Large-Sample Confidence Interval for a Population Mean. Small-Sample Confidence Interval for a Population Mean. Large-Sample Confidence Interval for a Population Proportion. Determining the Sample Size.

6. Inferences Based on a Single Sample: Tests of Hypotheses.

The Elements of a Test of Hypothesis. Large-Sample Test of Hypothesis about a Population Mean. Observed Significance Levels: p-Values. Small-Sample Test of Hypothesis about a Population Mean. Large-Sample Test of Hypothesis about a Population Proportion. Nonparametric Test about a Population Median (Optional).

7. Comparing Population Means.

Comparing Two Population Means: Independent Sampling. Comparing Two Population Means: Paired Difference Experiments. Determining the Sample Size. Nonparametric Test for Comparing Two Populations: Independent Sampling (Optional). A Nonparametric Test for Comparing Two Populations: Paired Difference Experiments (Optional). Comparing Three or More Population Means: Analysis of Variance (Optional).

8. Comparing Population Proportions.

Comparing Two Population Proportions: Independent Sampling. Determining the Sample Size. Comparing Population Proportions: Multinomial Experiment. Contingency Table Analysis.

9. Simple Linear Regression.

Probabalistic Models. Fitting the Model: The Least Squares Approach. Model Assumptions. An Estimator of …s2. Assessing the Utility of the Model: Making Inferences about the Slope …b1. The Coefficient of Correlation. The Coefficient of Determination. Using the Model for Estimation and Prediction. A Complete Example. A Nonparametric Test for Correlation (Optional).

Appendix A. Tables.

Random Numbers. Binomial Probabilities. Normal Curve Areas. Critical Values of t. Critical Values of …c2. Percentage Points of the F Distribution, …a= .10. Percentage Points of the F Distribution, …a=.05. Percentage Points of the F Distribution, …a=.025. Percentage Points of the F Distribution, …a=.01. Critical Values of T_L and T_U for the Wilcoxon Rank Sum Test: Independent Samples. Critical Values of T_O in the Wilcoxon Paired Difference Signed Rank Test. Critical Values of Spearman's Rank Correlation Coefficient.

Appendix B. Data Sets on CD-ROM that Accompany this Text.


Appendix C. Calculation Formulas for Analysis of Variance.


Short Answers to Selected Odd-Numbered Exercises.


Index.

Get First Course in Statistics, A, 8th Edition by James T. McClave, University of Florida Terry L. Sincich, University of South Florida

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