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| Volume 1 | |
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| A First Look at Statistics and MINITAB Why Study Statistics? | |
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| What is Statistics? | |
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| An Introduction to MINITAB | |
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| Describing Data: Graphical and Numerical Methods Graphical Methods for Quantitative Data: Frequency Distributions and Histograms | |
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| Graphical Methods for Quantitative Data: Dotplots and Stem-and-Leaf Displays | |
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| Graphical Methods for Qualitative Data: Bar and Pie Charts | |
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| Numerical Measures of Central Location | |
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| Numerical Measures of Variability | |
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| Understanding the Significance of Standard Deviation | |
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| Measures of Relative Position | |
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| Modeling Bivariate Data: Describing the Relationship Between Two Variables Straight Lines and the SS( ) Notation | |
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| Scatter Diagrams | |
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| Linear Regression and the Method of Least Squares | |
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| Correlation: Measuring the Usefulness of the Model | |
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| Probability: Measuring Uncertainty Probability, Sample Spaces and Events | |
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| Basic Techniques for Counting Sample Points | |
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| The Addition Rule of Probability | |
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| The Multiplication and Conditional Rules of Probability | |
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| The Complement Rule of Probability | |
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| Combining the Rules of Probability | |
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| Random Variables and Discrete Probability Random Variables | |
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| Discrete Probability Distributions | |
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| The Mean of a Discrete Random Variable | |
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| Measuring the Variability of a Random Variable | |
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| Special Discrete Probability Distributions Binomial Experiments | |
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| The Binomial Probability Distribution | |
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| The Mean and the Standard Deviation of a Binomial Random Variable | |
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| The Hypergeometric Probability Distribution (Optional). The Poisson Probability Distribution (Optional) | |
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| Normal Probability Distributions Probability Distributions of Continuous Random Variables | |
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| Normal Probability Distributions | |
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| Applications of Normal Distributions | |
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| Using Normal Distributions to Approximate Binomial Distributions | |
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| Sampling Methods and Sampling Distributions Random Sampling | |
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| Other Scientific Sampling Methods | |
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| Sampling Distributions | |
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| The Central Limit Theorem | |
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| Applications of the Central Limit Theorem | |
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| Estimating Means, Proportions and Variances: Single Sample Basic Concepts of Estimating Population Parameters | |
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| Confidence Interval for a Mean: Large Sample Student''s Probability Distributions | |
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| Confidence Interval for a Mean: Small Sample | |
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| Confidence Interval for a Proportion: Large Sample | |
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| Determining the Required Sample Size | |
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| Chi-Square Probability Distributions Confidence Interval for a Variance | |
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| Tests of Hypotheses: Single Sample Basic Concepts of Testing Statistical Hypotheses | |
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| Hypothesis Test for a Mean: Large Sample | |
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| Hypothesis Test for a Mean: Small Sample | |
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| Hypothesis Test for a Proportion: Large Sample | |
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| Hypothesis Test for a Variance | |
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| Using p-Values to Report Test Results | |
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| Tests of Hypotheses and Estimation: Two Samples Large-Sample Inferences for Two Means: Independent Samples | |
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| Small-Sample Inferences for Two Means: Independent Samples and Equal Variances | |
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| Small-Sample Inferences for Two Means: Independent Samples and Unequal Variances (Optional). Inferences for Two Means: Paired Samples | |
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| Large Sample Inferences for Two Proportions | |
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| Determining Required Sample Sizes | |
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| F Probability Distributions | |
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| Inferences for Two Variances | |
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| Chi-Square Tests for Analyzing Count Data Count Data and the Chi-Square Statistic | |
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| Hypothesis Test for a Multinomial Experiment | |
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| Hypothesis Test for a Contingency Table | |
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| Hypothesis Test for Two or More Proportions | |
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| Volume II | |
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| Analysis of Variance The Analysis of Variance Technique | |
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| The Analysis of Variance Table and Computing Formulas | |
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| Applications of the One-Way Analysis of Variance | |
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| Estimation of Means | |
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| Randomized Block Designs and the Analysis of Variance | |
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| Linear Regression Analysis The Simple Linear Model and Related Assumptions | |
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| Fitting the Model by the Method of Least Squares | |
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| Inferences for the Slope to Assess the Usefulness of the Model | |
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| The Coefficients of Correlation and Determination to Measure the Usefulness of the Model | |
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