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| Descriptive Statistics | |
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| Introduction to Statistics | |
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| Stumbling Blocks to Statistics | |
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| A Brief Look at the History of Statistics | |
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| Benefits of a Course in Statistics | |
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| General Field of Statistics | |
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| Graphs and Measures of Central Tendency | |
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| Graphs | |
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| Measures of Central Tendency | |
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| Appropriate Use of the Mean, the Median, and the Mode | |
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| Variability | |
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| Measures of Variability | |
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| Graphs and Variability | |
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| Questionnaire Percentages | |
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| The Normal Curve and z Scores | |
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| The Normal Curve. z Scores | |
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| Translating Raw Scores into z Scores. z Score Translations in Practice | |
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| Fun with Your Calculator | |
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| z Scores Revisited: t Scores and Other Normal Curve Transformations | |
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| Other Applications of the z Score | |
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| The Percentile Table. t Scores | |
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| Normal Curve Equivalents | |
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| Stanines | |
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| Grade-Equivalent Scores: A Note of Caution | |
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| The Importance of the z Score | |
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| Probability | |
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| The Definition of Probability | |
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| Probability and Percentage Areas of the Normal Curve | |
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| Combining Probabilities for Independent Events | |
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| A Reminder about Logic | |
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| Inferential Statistics | |
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| Statistics and Parameters | |
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| Generalizing from the Few to the Many | |
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| Key Concepts of the Inferential Statistics | |
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| Techniques of Sampling | |
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| Exit Polling | |
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| Sampling Distributions | |
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| Back to z | |
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| Some Words of Encouragement | |
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| Parameter Estimates and Hypothesis Testing | |
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| The Standard Deviation Revisited | |
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| Estimating the Standard Error of the Mean | |
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| Estimating the Popular Mean: Interval Estimates and Hypothesis Testing | |
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| The t ratio | |
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| The Type 1 Error | |
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| Alpha Levels | |
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| Effect Size | |
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| Interval Estimates: No Hypothesis Needed | |
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| The Fundamentals of Research Methodology | |
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| Research Strategies | |
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| Independent and Dependent Variables | |
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| The Cause-and-Effect Trap | |
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| Theory of Measurement | |
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| Research: Experimental versus Post-Facto | |
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| The Experimental Method: The Case of Cause and Effect | |
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| Creating Equivalent Groups: The True Experiment | |
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| Designing the True Experiment | |
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| The Hawthorne Effect | |
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| Repeated Measure Designs with Separate Control Groups | |
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| Requirements for the True Experiment | |
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| Post-Facto Research | |
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| Combination Research | |
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| Research Errors | |
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| Experimental Error: Failure to Use an Adequate Control Group | |
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| Post-Facto Errors | |
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| Meta-Analysis | |
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| Methodology as a Basis for More Sophisticated Techniques | |
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| The Hypothesis of Difference | |
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| Sampling Distribution of Differences | |
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| Estimated Standard Error of Difference | |
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| Two-Sample t Test for Independent Samples | |
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| Significance | |
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| Two-Tail t Table | |
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| Alpha and Confidence Levels | |
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| Confidence Interval for Differences Between Two Independent Samples | |
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| The Minimum Difference | |
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| Outliers | |
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| One-Tail t Test | |
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| Importance of Having at Least Two Samples | |
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| Power | |
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| Effect Size | |
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| The Hypothesis of Association: Correlation | |
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| Cause and Effect | |
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| The Pearson r | |
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| Interclass versus Intraclass | |
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| Correlation Matrix | |
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| The Spearman r | |
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| An Important Difference between Correlation Coefficient and the t Test | |
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| Analysis of Variance | |
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| Advantages of ANOVA | |
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| Analyzing the Variance | |
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| Applications of ANOVA | |
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| The Factorial ANOVA | |
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| Eta squared and d | |