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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 | |
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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