Statistics - McClave, James T.; Sincich, Terry (Harlow : Pearson, 2014)
1. Statistics, Data, and Statistical Thinking 1.1 The Science of Statistics 1.2 Types of Statistical Applications 1.3 Fundamental Elements of Statistics 1.4 Types of Data 1.5 Collecting Data 1.6 The Role of Statistics in Critical Thinking Statistics in Action: Social Media Networks and the Millennial Generation Using Technology: Creating and Listing Data 2. Methods for Describing Sets of Data 2.1 Describing Qualitative Data 2.2 Graphical Methods for Describing Quantitative Data 2.3 Summation Notation 2.4 Numerical Measures of Central Tendency 2.5 Numerical Measures of Variability 2.6 Interpreting the Standard Deviation 2.7 Numerical Measures of Relative Standing 2.8 Methods for Detecting Outliers: Box Plots and z-Scores 2.9 Graphing Bivariate Relationships (Optional) 2.10 Distorting the Truth with Descriptive Techniques Statistics In Action: Body Image Dissatisfaction: Real or Imagined? Using Technology: Describing Data 3. Probability 3.1 Events, Sample Spaces, and Probability 3.2 Unions and Intersections 3.3 Complementary Events 3.4 The Additive Rule and Mutually Exclusive Events 3.5 Conditional Probability 3.6 The Multiplicative Rule and Independent Events 3.7 Random Sampling 3.8 Some Additional Counting Rules (Optional) 3.9 Bayes' Rule (Optional) Statistics In Action: Lotto Buster! -Can You Improve Your Chances of Winning the Lottery? Using Technology: Generating a Random Sample 4. Discrete Random Variables 4.1 Two Types of Random Variables 4.2 Probability Distributions for Discrete Random Variables 4.3 Expected Values of Discrete Random Variables 4.4 The Binomial Random Variable 4.5 The Poisson Random Variable (Optional) 4.6 The Hypergeometric Random Variable (Optional) Statistics in Action: Probability in a Reverse Cocaine Sting- Was Cocaine Really Sold? Using Technology: Discrete Probabilities 5. Continuous Random Variables 5.1 Continuous Probability Distributions 5.2 The Uniform Distribution 5.3 The Normal Distribution 5.4 Descriptive Methods for Assessing Normality 5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional) 5.6 The Exponential Distribution (Optional) Statistics in Action: Super Weapons Development - Is the Hit Ratio Optimized? Using Technology: Continuous Random Variables, Probabilities, and Normal Probability Plots 6. Sampling Distributions 6.1 What is a Sampling Distribution? 6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance 6.3 The Sampling Distribution of (x-bar) and the Central Limit Theorem Statistics in Action: The Insomnia Pill-Will It Take Less Time to Fall Asleep? Using Technology: Simulating a Sampling Distribution 7. Inferences Based on a Single Sample: Estimation with Confidence Intervals 7.1 Identifying and Estimating the Target Parameter 7.2 Confidence Interval for a Population Mean: Normal (z) Statistic 7.3 Confidence Interval for a Population Mean: Student's t-statistic 7.4 Large-Sample Confidence Interval for a Population Proportion 7.5 Determining the Sample Size 7.6 Confidence Interval for a Population Variance (Optional) Statistics in Action: Medicare Fraud Investigations Using Technology: Confidence Intervals 8. Inferences Based on a Single Sample: Tests of Hypothesis 8.1 The Elements of a Test of Hypothesis 8.2 Formulating Hypotheses and Setting Up the Rejection Region 8.3 Test of Hypothesis About a Population Mean: Normal (z) Statistic 8.4 Observed Significance Levels: p-Values 8.5 Test of Hypothesis About a Population Mean: Student's t-statistic 8.6 Large-Sample Test of Hypothesis About a Population Proportion 8.7 Calculating Type II Error Probabilities: More About ss (Optional) 8.8 Test of Hypothesis About a Population Variance (Optional) Statistics in Action: Diary of a Kleenex User-How Many Tissues in a Box? Using Technology: Tests of Hypothesis 9. Inferences Based on a Two Samples: Confidence Intervals and Tests of Hypotheses 9.1 Identifying the Target Parameter 9.2 Comparing Two Population Means: Independent Sampling 9.3 Comparing Two Population Means: Paired Difference Experiments 9.4 Comparing Two Population Proportions: Independent Sampling 9.5 Determining the Sample Size 9.6 Comparing Two Population Variances: Independent Sampling (Optional) Statistics in Action: Zixit Corp. vs. Visa USA Inc.-A Libel Case Using Technology: Two-Sample Inferences 10. Analysis of Variance: Comparing More Than Two Means 10.1 Elements of a Designed Study 10.2 The Completely Randomized Design: Single Factor 10.3 Multiple Comparisons of Means 10.4 The Randomized Block Design 10.5 Factorial Experiments: Two Factors Statistics in Action: On the Trail of the Cockroach: Do Roaches Travel at Random? Using Technology: Analysis of Variance 11. Simple Linear Regression 11.1 Probabilistic Models 11.2 Fitting the Model: The Least Squares Approach 11.3 Model Assumptions 11.4 Assessing the Utility of the Model: Making Inferences About the Slope ss1 11.5 The Coefficients of Correlation and Determination 11.6 Using the Model for Estimation and Prediction 11.7 A Complete Example Statistics in Action: Can "Dowsers" Really Detect Water? Using Technology: Simple Linear Regression 12. Multiple Regression and Model Building 12.1 Multiple Regression Models 12.2 The First-Order Model: Inferences About the Individual ss-Parameters 12.3 Evaluating the Overall Utility of a Model 12.4 Using the Model for Estimation and Prediction 12.5 Model Building: Interaction Models 12.6 Model Building: Quadratic and other Higher-Order Models 12.7 Model Building: Qualitative (Dummy) Variable Models 12.8 Model Building: Models with both Quantitative and Qualitative Variables 12.9 Model Building: Comparing Nested Models (Optional) 12.10 Model Building: Stepwise Regression (Optional) 12.11 Residual Analysis: Checking the Regression Assumptions 12.12 Some Pitfalls: Estimability, Multicollinearity, and Extrapolation Statistics in Action: Modeling Condo Sales: Are There Differences in Auction Prices? Using Technology: Multiple Regression 13. Categorical Data Analysis 13.1 Categorical Data and the Multinomial Distribution 13.2 Testing Categorical Probabilities: One-Way Table 13.3 Testing Categorical Probabilities: Two-Way (Contingency) Table 13.4 A Word of Caution About Chi-Square Tests Statistics in Action: College Students and Alcohol-Is Drinking Frequency Related to Amount? Using Technology: Chi-Square Analyses Appendix A. Tables Table I. Random Numbers Table II. Binomial Probabilities Table III. Poisson Probabilities Table IV. Normal Curve Areas Table V. Exponentials Table VI. Critical Values of t Table VII. Critical Values of x2 Table VIII. Percentage Points of the F Distribution, a=.10 Table IX. Percentage Points of the F Distribution, a=.05 Table X. Percentage Points of the F Distribution, a=.025 Table XI. Percentage Points of the F Distribution, a=.01 Table XII. Critical Values of TL and TU for the Wilcoxon Rank Sum Test Table XIII. Critical Values of T0 in the Wilcoxon Signed Rank Test Table XIV. Critical Values of Spearman's Rank Correlation Coefficient Appendix B. Calculation Formulas for Analysis of Variance Short Answers to Selected Odd-Numbered Exercises *This chapter is included on the CD-ROM that comes with the textbook
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Includes bibliographical references and index.
Keywords: Statistics