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| Statistics, Data, and Statistical Thinking | |
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| the Science of Statistics | |
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| Types of Statistical Applications | |
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| Fundamental Elements of Statistics | |
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| Types of Data | |
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| Collecting Data | |
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| the Role of Statistics in Critical Thinking | |
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| Statistics in Action: Social Media Networks and the Millennial Generation | |
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| Using Technology: Creating and Listing Data | |
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| Methods for Describing Sets of Data | |
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| Describing Qualitative Data | |
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| Graphical Methods for Describing Quantitative Data | |
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| Summation Notation | |
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| Numerical Measures of Central Tendency | |
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| Numerical Measures of Variability | |
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| Interpreting the Standard Deviation | |
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| Numerical Measures of Relative Standing | |
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| Methods for Detecting Outliers: Box Plots and z-Scores | |
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| Graphing Bivariate Relationships (Optional) | |
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| Distorting the Truth with Descriptive Techniques | |
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| Statistics in Action: Body Image Dissatisfaction: Real or Imagined? | |
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| Using Technology: Describing Data | |
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| Probability | |
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| Events, Sample Spaces, and Probability | |
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| Unions and Intersections | |
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| Complementary Events | |
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| the Additive Rule and Mutually Exclusive Events | |
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| Conditional Probability | |
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| the Multiplicative Rule and Independent Events | |
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| Random Sampling | |
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| Some Additional Counting Rules (Optional) | |
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| Bayes' Rule (Optional) | |
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| Statistics in Action: Lotto Buster! -Can You Improve your Chances of Winning the Lottery? | |
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| Using Technology: Generating a Random Sample | |
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| Discrete Random Variables | |
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| Two Types of Random Variables | |
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| Probability Distributions for Discrete Random Variables | |
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| Expected Values of Discrete Random Variables | |
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| the Binomial Random Variable | |
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| the Poisson Random Variable (Optional) | |
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| the Hypergeometric Random Variable (Optional) | |
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| Statistics in Action: Probability in a Reverse Cocaine Sting- Was Cocaine Really Sold? | |
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| Using Technology: Discrete Probabilities | |
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| Continuous Random Variables | |
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| Continuous Probability Distributions | |
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| the Uniform Distribution | |
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| the Normal Distribution | |
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| Descriptive Methods for Assessing Normality | |
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| Approximating a Binomial Distribution with a Normal Distribution (Optional) | |
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| the Exponential Distribution (Optional) | |
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| Statistics in Action: Super Weapons Development - is the Hit Ratio Optimized? | |
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| Using Technology: Continuous Random Variables, Probabilities, and Normal Probability Plots | |
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| Sampling Distributions | |
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| What is a Sampling Distribution? | |
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| Properties of Sampling Distributions: Unbiasedness and Minimum Variance | |
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| the Sampling Distribution of (x-bar) and the Central Limit Theorem | |
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| Statistics in Action: the Insomnia Pill-Will It Take Less Time to Fall Asleep? | |
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| Using Technology: Simulating a Sampling Distribution | |
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| Inferences Based on a Single Sample: Estimation with Confidence Intervals | |
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| Identifying and Estimating the Target Parameter | |
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| Confidence Interval for a Population Mean: Normal (z) Statistic | |
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| Confidence Interval for a Population Mean: Student's t-statistic | |
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| Large-Sample Confidence Interval for a Population Proportion | |
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| Determining the Sample Size | |
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| Confidence Interval for a Population Variance (Optional) | |
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| Statistics in Action: Medicare Fraud Investigations | |
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| Using Technology: Confidence Intervals | |
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| Inferences Based on a Single Sample: Tests of Hypothesis | |
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| the Elements of a Test of Hypothesis | |
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| Formulating Hypotheses and Setting Up the Rejection Region | |
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| Test of Hypothesis About a Population Mean: Normal (z) Statistic | |
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| Observed Significance Levels: p-Values | |
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| Test of Hypothesis About a Population Mean: Student's t-statistic | |
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| Large-Sample Test of Hypothesis About a Population Proportion | |
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| Calculating Type II Error Probabilities: More About � (Optional) | |
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| Test of Hypothesis About a Population Variance (Optional) | |
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| Statistics in Action: Diary of a Kleenex User-How Many Tissues in a Box? | |
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| Using Technology: Tests of Hypothesis | |
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| Inferences Based on a Two Samples: Confidence Intervals and Tests of Hypotheses | |
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| Identifying the Target Parameter | |
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| Comparing Two Population Means: Independent Sampling | |
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| Comparing Two Population Means: Paired Difference Experiments | |
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| Comparing Two Population Proportions: Independent Sampling | |
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| Determining the Sample Size | |
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| Comparing Two Population Variances: Independent Sampling (Optional) | |
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| Statistics in Action: Zixit Corp. vs. Visa USA Inc.-A Libel Case | |
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| Using Technology: Two-Sample Inferences | |
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| Analysis of Variance: Comparing More Than Two Means | |
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| Elements of a Designed Study | |
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| the Completely Randomized Design: Single Factor | |
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| Multiple Comparisons of Means | |
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| the Randomized Block Design | |
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| Factorial Experiments: Two Factors | |
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| Statistics in Action: on the Trail of the Cockroach: Do Roaches Travel at Random? | |
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| Using Technology: Analysis of Variance | |
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| Simple Linear Regression | |
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| Probabilistic Models | |
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| Fitting the Model: the Least Squares Approach | |
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| Model Assumptions | |
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| Assessing the Utility of the Model: Making Inferences About the Slope �1 | |
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| the Coefficients of Correlation and Determination | |
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| Using the Model for Estimation and Prediction | |
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| A Complete Example | |
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| Statistics in Action: Can "Dowsers" Really Detect Water? | |
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| Using Technology: Simple Linear Regression | |
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| Multiple Regression and Model Building | |
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| Multiple Regression Models | |
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| the First-Order Model: Inferences About the Individual �-Parameters | |
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| Evaluating the Overall Utility of a Model | |
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| Using the Model for Estimation and Prediction | |
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| Model Building: Interaction Models | |
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| Model Building: Quadratic and other Higher-Order Models | |
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| Model Building: Qualitative (Dummy) Variable Models | |
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| Model Building: Models with both Quantitative and Qualitative Variables | |
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| Model Building: Comparing Nested Models (Optional) | |
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| Model Building: Stepwise Regression (Optional) | |
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| Residual Analysis: Checking the Regression Assumptions | |
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| Some Pitfalls: Estimability, Multicollinearity, and Extrapolation | |
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| Statistics in Action: Modeling Condo Sales: are There Differences in Auction Prices? | |
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| Using Technology: Multiple Regression | |
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| Categorical Data Analysis | |
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| Categorical Data and the Multinomial Distribution | |
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| Testing Categorical Probabilities: One-Way Table | |
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| Testing Categorical Probabilities: Two-Way (Contingency) Table | |
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| A Word of Caution About Chi-Square Tests | |
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| Statistics in Action: College Students and Alcohol-Is Drinking Frequency Related to Amount? | |
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| Using Technology: Chi-Square Analyses | |
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| Nonparametric Statistics | |
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| Introduction: Distribution-Free Tests | |
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| Single Population Inferences | |
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| Comparing Two Populations: Independent Samples | |
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| Comparing Two Populations: Paired Difference Experiment | |
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| Comparing Three or More Populations: Completely Randomized Design | |
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| Comparing Three or More Populations: Randomized Block Design | |
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| Rank Correlation | |
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| Statistics in Action: How Vulnerable are Wells to Groundwater Contamination? | |
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| Using Technology: Nonparametric Analyses | |
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| Tables | |
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| Random Numbers | |
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| Binomial Probabilities | |
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| Poisson Probabilities | |
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| Normal Curve Areas | |
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| Exponentials | |
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| Critical Values of t | |
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| Critical Values of x2 | |
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| Percentage Points of the F Distribution, �=.10 | |
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| Percentage Points of the F Distribution, �=.05 | |
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| Percentage Points of the F Distribution, �=.025 | |
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| Percentage Points of the F Distribution, �=.01 | |
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| Critical Values of TL and TU for the Wilcoxon Rank Sum Test | |
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| Critical Values of T0 in the Wilcoxon Signed Rank Test | |
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| Critical Values of Spearman's Rank Correlation Coefficient | |
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| Calculation Formulas for Analysis of Variance | |
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| Short Answers to Selected Odd-Numbered Exercises | |