Introduction | |
The Nature of Statistics | |
Case Study: Top Films of All Time | |
Two Kinds of Statistics | |
The Technology Center | |
Simple Random Sampling | |
Other Sampling Designs | |
Experimental Designs | |
Descriptive Statistics | |
Organizing Data | |
Case Study: Preventing Infant Mortality | |
Variables and Data | |
Grouping Data | |
Graphs and Charts | |
Stem-and-Leaf Diagrams | |
Distribution Shapes; Symmetry and Skewness | |
Misleading Graphs | |
Descriptive Measures | |
Case Study: New York Yankees Y2K Salaries | |
Measures of Center | |
The Sample Mean | |
Measures of Variation; the Sample Standard Deviation | |
The Five-Number Summary; Boxplots | |
Descriptive Measures for Populations; Use of Samples | |
Descriptive Methods in Regression and Correlation | |
Case Study: Fat Consumption and Prostate Cancer | |
Linear Equations With One Independent Variable | |
The Regression Equation | |
The Coefficient of Determination | |
Linear Correlation | |
Probability, Random Variables, and Sampling Distributions | |
Probability and Random Variables | |
Case Study: The Powerball | |
Probability Basics | |
Events | |
Some Rules of Probability | |
Discrete Random Variables and Probability Distributions | |
The Mean and Standard Deviation of a Discrete Random Variable | |
The Binomial Distribution | |
The Normal Distribution | |
Case Study: Chest Sizes of Scottish Militiamen | |
Introducing Normally Distributed Variables | |
Areas Under the Standard Normal Curve | |
Working With Normally Distributed Variables | |
Assessing Normality; Normal Probability Plots | |
The Sampling Distribution of the Sample Mean | |
Case Study: The Chesapeake and Ohio Freight Study | |
Sampling Error; the Need for Sampling Distributions | |
The Mean and Standard Deviation of x | |
The Sampling Distribution of the Sample Mean | |
Inferential Statistics | |
Confidence Intervals for One Population Mean | |
Case Study: The Chips Ahoy! 1,000 Chips Challenge | |
Estimating a Population Mean | |
Confidence Intervals for One Population Mean When | |
Margin of Error | |
Confidence Intervals for One Population Mean When | |
Hypothesis Tests for One Population Mean | |
Case Study: Sex and Sense of Direction | |
The Nature of Hypothesis Testing | |
Terms, Errors, and Hypotheses | |
Hypothesis Tests for One Population Mean When | |
P-Values | |
Hypothesis Tests for One Population Mean When | |
Inferences for Two Population Means | |
Case Study: Breast Milk and IQ | |
The Sampling Distribution of the Difference Between Two Sample Means for Independent Samples | |
Inferences for Two Population Means Using Independent Samples: Standard Deviations Assumed Equal | |
Inferences for Two Population Means Using Independent Samples: Standard Deviations Not Assumed Equal | |
Inferences for Two Population Means Using Paired Samples | |
Inferences for Population Proportions | |
Case Study: Double-Dipping ATM Fees | |
Confidence Intervals for One Population Proportion | |
Hypothesis Tests for One Population Proportion | |
Inferences for Two Population Proportions Using Independent Samples | |
Chi-Square Procedures | |
Case Study: Road Rage | |
The Chi-Square Distribution | |
Chi-Square Goodness-Of-Fit Test | |
Contingency Tables; Association | |
Chi-Square Independence Test | |
Analysis of Variance (ANOVA) | |
Case Study: Heavy Drinking Among College Students | |
The F-Distribution | |
One-Way ANOVA: The Logic | |
One-Way ANOVA: The Procedure | |
Inferential Methods In Regression and Correlation | |
Case Study: Fat Consumption and Prostate Cancer | |
The Regression Model | |
Analysis of Residuals | |
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