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| Statistics Success Stories and Cautionary Tales | |
| What is Statistics? Seven Statistical Stories with Morals | |
| The Common Elements in the Seven Stories | |
| Turning Data Into Information | |
| Raw Data | |
| Types of Data | |
| Summarizing One or Two Categorical Variables | |
| Finding Information in Quantitative Data | |
| Pictures for Quantitative Data | ... MORE |
| Numerical Summaries of Quantitative Variables | |
| Bell-Shaped Distributions of Numbers | |
| Gathering Useful Information | |
| Description or Decision? Using Data Wisely | |
| Speaking the Language of Research Studies | |
| Designing a Good Experiment | |
| Designing a Good Observational Study | |
| Difficulties and Disasters in Experiments and Observational Studies | |
| Sampling: Surveys And How To Ask Questions | |
| The Beauty of Sampling | |
| Sampling Methods | |
| Difficulties and Disasters in Sampling | |
| How to Ask Survey Questions | |
| Relationships Between Quantitative Variables | |
| Looking for Patterns With Scatterplots | |
| Describing Linear Patterns With a Regression Line | |
| Measuring Strength and Direction With a Regression Line | |
| Why Answers May Not Make Sense | |
| Correlation Does Not Prove Causation | |
| Relationships Between Categorical Variables | |
| Displaying Relationships Between Categorical Variables | |
| Risk, Relative Risk, Odds Ratio, and Increased Risk | |
| Misleading Statistics About Risk | |
| The Effect of a Third Variable and Simpson?s Paradox | |
| Assessing the Statistical Significance of a 2 x 2 Table | |
| Probability | |
| Random Circumstances | |
| Interpretations of Probability | |
| Probability Definitions and Relationships | |
| Basic Rules for Finding Probabilities | |
| Strategies for Finding Complicated Probabilities | |
| Using Simulation to Estimate Probabilities | |
| Coincidences and Intuitive Judgments About Probability | |
| Random Varaibles | |
| What is a Random Variable? Discrete Random Variables | |
| Expectations for Random Variables | |
| Binomial Random Variables | |
| Continuous Random Variables | |
| Normal Random Variables | |
| Approximating Binominal Distribution Probabilities | |
| Sums, Differences, and Combinations of Random Variables | |
| Means and Proportions as Random Variables | |
| Understanding Dissimilarity Among Samples | |
| Sampling Distributions for Sample Proportions | |
| What to Expect of Sample Means | |
| What to Expect in Other Situations: Central Limit Theorem | |
| Sampling Distribution for Any Statistic | |
| Standardized Statistics | |
| Student?s t-Distribution: Replacing = with s | |
| Statistical Inference | |
| Estimating Proportions With Confidence | |
| The Language and Notation of Estimation | |
| Margin of Error | |
| Confidence Intervals | |
| Calculating a Margin of Error for 95% Confidence | |
| General Theory of Confidence Intervals for a Proportion | |
| Choosing a Sample Size For a Survey | |
| Using Confidence Intervals to Guide Decisions | |
| Testing Hypotheses About Proportions | |
| Formulating Hypothesis Statements | |
| The Logic of Hypothesis Testing: What if the Null is True? Reaching a Conclusion About the Two Hypotheses | |
| Testing Hypotheses About a Proportion | |
| The Role of Sample Size in Statistical Significance | |
| Real Importance versus Statistical Significance | |
| What Can Go Wrong: The Two Types of Errors | |
| More About Confidence Intervals | |
| Examples of Different Estimation Situations | |
| Standard Errors | |
| Approximate 95% Confidence Intervals | |
| General Confidence Intervals for One Mean or Paired Data | |
| General Confidence Intervals for the Difference Between Two Means (Independent Samples) | |
| The Difference Between Two Proportions (Independent Samples) | |
| Understanding Any Confidence Interval | |
| More About Significance Tests | |
| The General Ideas of Significance Testing | |
| Testing Hypotheses About One Mean or Paired Data | |
| Testing the Difference Between Two Means (Independent Samples) | |
| Testing the Difference Between Two Population Proportions | |
| The Relationship Between Significance Tests and Confidence Intervals | |
| The Two Types of Errors and Their Probabilities | |
| Evaluating Significance in Research Reports | |
| More About Regression | |
| Sample and Population Regression Models | |
| Estimating the Standard Deviation for Regression | |
| Inference About the L | |
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