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| Defining The Problem | |
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| Statistics and the Scientific Method | |
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| Introduction | |
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| Why Study Statistics? Some Current Applications of Statistics | |
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| A Note to the Student | |
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| Staying Focused | |
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| Collecting Data | |
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| Collecting Data Using Surveys and Scientific Studies | |
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| Introduction | |
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| Surveys | |
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| Sampling Designs for Surveys | |
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| Scientific Studies | |
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| Experimental Designs for Scientific Studies | |
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| Observational Studies | |
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| Data Management: Preparing Data for Summarization and Analysis (Optional) | |
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| Staying Focused | |
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| Summarizing Data | |
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| Summarizing Data | |
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| Introduction | |
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| Calculators, Computers, and Software Systems | |
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| Summarizing Data on a Single Variable: Graphical Methods | |
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| Summarizing Data on a Single Variable: Measures of Central Tendency | |
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| Summarizing Data on a Single Variable: Measures of Variability | |
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| The Boxplot | |
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| Summarizing Data from More than One Variable | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Probability and Probability Distributions | |
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| How Probability Can Be Used in Making Inferences | |
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| Finding the Probability of an Event | |
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| Basic Event Relations and Probability Laws | |
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| Conditional Probability and Independence | |
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| Bayes+ Formula | |
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| Variables: Discrete and Continuous | |
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| Probability Distributions for Discrete Random Variables | |
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| A Useful Discrete Random Variable: The Binomial | |
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| Probability Distributions for Continuous Random Variables | |
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| A Useful Continuous Random Variable: The Normal Distribution | |
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| Random Sampling | |
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| Sampling Distributions | |
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| Normal Approximation to the Binomial | |
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| MINITAB Instructions (Optional) | |
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| Staying Focused | |
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| Analyzing Data, Interpreting The Analyses, And Communicating The Results | |
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| Inferences About Population Central Values | |
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| Introduction | |
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| Estimation of 8 | |
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| Choosing the Sample Size for Estimating 8 | |
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| A Statistical Test for 8 | |
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| Choosing the Sample Size for Testing 8 | |
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| The Level of Significance of a Statistical Test | |
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| Inferences about 8 for Normal Population, = Unknown | |
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| Inferences about Median | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Inferences Comparing Two Population Central Values | |
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| Introduction | |
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| Inferences about 81+82: Independent Samples | |
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| A Nonparametric Alternative: The Wilcoxon Rank Sum Test | |
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| Inferences about 81+82: Paired Data | |
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| A Nonparametric Alternative: The Wilcoxon Signed-Rank Test | |
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| Choosing Sample Sizes for Inferences about 81+82 | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Inferences About Population Variances | |
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| Introduction | |
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| Estimation and Tests for a Population Variance | |
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| Estimation and Tests for Comparing Two Population Variances | |
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| Tests for Comparing t >2 Population Variances | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| The Completely Randomized Design | |
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| Introduction | |
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| The Model for Observations in a Completely Randomized Design | |
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| Analyzing Data from a Completely Randomized Design: An Analysis of Variances | |
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| Checking on the AOV Conditions | |
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| A Nonparametric Alternative: The Kruskal+Wallis Test | |
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| Multiple Comparisons | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| More Complicated Experimental Designs | |
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| Introduction | |
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| Randomized Complete Block Design | |
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| Latin Square Design | |
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| Factorial Treatment Structure in a Completely Randomized Design | |
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| Factorial Treatment Structure in a Randomized Complete Block Design | |
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| Estimation of Treatment Differences and Comparisons of Treatment Means | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Categorical Data | |
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| Introduction | |
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| Inferences About a Population Proportion =.Inferences About the Difference Between Two Population Proportions =1+ =2 | |
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| Inferences About Several Proportions: Chi-Square Goodness-of-Fit Test | |
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| Contingency Tables: Tests for Independence and Homogeneity | |
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| Odds and Odds Ratios | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Linear Regression and Correlation | |
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| Introduction | |
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| Estimating Model Parameters | |
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| Inferences about Regression Parameters | |
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| Predicting New y Values Using Regression | |
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| Examining Lack of Fit in Linear Regression | |
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| The Inverse Regression Problem (Calibration) | |
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| Correlation | |
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| Encounters with Real Data | |
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| Staying Focused | |
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| Multiple Regression | |
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| Introduction | |
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| Est | |