Practical Statistics for Engineering and the Sciences

1. DATA AND DISTRIBUTIONS. Populations, Samples, and Processes. Visual Displays for Univariate Data. Describing Distributions. The Normal Distribution. Other Continuous Distributions. Several Useful Discrete Distributions. 2. NUMERICAL SUMMARY MEASURES. Measures of Center. Measures of Variability. More Detailed Summary Quantities. Quantile Plots. 3. BIVARIATE AND MULTIVARIATE DATA. Scatter Plots. Correlation. Fitting a Straight Line. Nonlinear Relationships. Using More than One Predictor. Joint Distributions. 4. PRODUCING DATA. Operational Definitions. Data from Samples. Data from Experiments. Measurement Systems. 5. STATISTICS AND SAMPLING DISTRIBUTIONS. Chance Experiments. Probability Concepts. Conditional Probability and Independence. Random Variables. Sampling Distributions. Describing Sampling Distributions. 6. QUALITY CONTROL. Terminology. How Control Charts Work. Control Charts for Process Mean Variation. Process Capability Analysis. Control Charts for Attribute Data. 7. ESTIMATION AND STATISTICAL INTERVALS. Point Estimations . Large-Sample Confidence Intervals for a Population Mean. More Large-Sample Intervals. Small-Sample Intervals Based on a Normal Population Distribution. Intervals for H1 - H2 Based on a Normal Population Distribution. Bootstrap Intervals. Further Aspects of Estimation. 8. TESTING STATISTICAL HYPOTHESES. Hypotheses and Test Procedures. Tests Concerning Hypotheses about Means. Testing Concerning Hypotheses about a Categorical Population. Testing the Form of a Distribution. Further Aspects of Hypothesis Testing. 9. THE ANALYSIS OF VARIANCE. Terminology and Concepts. Single-Factor ANOVA (including effects plots). Interpreting ANOVA Results. Randomized Block Experiments. 10. EXPERIMENTAL DESIGN. Terminology an Concepts. Two-Factor Designs. Multi-Factor Designs. 2k Designs. Fractional Factorial Designs. 11. INFERENCES IN REGRESSION ANALYSIS. Regression Models Involving a Single Independent Variable. Inferences about the Slope Coefficient b. Inferences Based on the Estimated Regression Line. Multiple Regression Models. Inferences in Multiple Regression. Further Aspects of Regression Analysis.