Introduction to Probability and Statistics, Canadian 4th edition

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• Chapter 1: Describing Data with Graphs
  • 1.1: Variables and Data
  • 1.2: Types of Variables
  • 1.3: Graphs for Categorical Data
  • 1.4: Graphs for Quantitative Data
  • 1.5: Relative Frequency Histograms
  • 1: Supplementary Exercises
  • 1: Test Bank
  
  
• Chapter 2: Describing Data with Numerical Measures
  • 2.1: Describing a Set of Data with Numerical Measures
  • 2.2: Measures of Centre
  • 2.3: Measures of Variability
  • 2.4: On the Practical Significance of the Standard Deviation
  • 2.5: A Check on the Calculation of s
  • 2.6: Measures of Relative Standing
  • 2.7: The Five-Number Summary and the Box Plot
  • 2: Supplementary Exercises
  • 2: Test Bank
  
  
• Chapter 3: Describing Bivariate Data
  • 3.1: Bivariate Data
  • 3.2: Graphs for Qualitative Variables
  • 3.3: Scatterplots for Two Quantitative Variables
  • 3.4: Numerical Measures for Quantitative Bivariate Data
  • 3: Supplementary Exercises
  • 3: Test Bank
  
  
• Chapter 4: Probability and Probability Distributions
  • 4.1: The Role of Probability in Statistics
  • 4.2: Events and the Sample Space
  • 4.3: Calculating Probabilities Using Simple Events
  • 4.4: Useful Counting Rules (Optional)
  • 4.5: Event Relations and Probability Rules
  • 4.6: Independence, Conditional Probability, and the Multiplication Rule
  • 4.7: Bayes' Rule (Optional)
  • 4.8: Discrete Random Variables and Their Probability Distributions
  • 4: Supplementary Exercises
  • 4: Test Bank
  
  
• Chapter 5: Several Useful Discrete Distributions
  • 5.1: Introduction
  • 5.2: The Binomial Probability Distribution
  • 5.3: The Poisson Probability Distribution
  • 5.4: The Hypergeometric Probability Distribution
  • 5: Supplementary Exercises
  • 5: Test Bank
  
  
• Chapter 6: The Normal Probability Distribution
  • 6.1: Probability Distributions for Continuous Random Variables
  • 6.2: The Normal Probability Distribution
  • 6.3: Tabulated Areas of the Normal Probability Distribution
  • 6.4: The Normal Approximation to the Binomial Probability Distribution (Optional)
  • 6: Supplementary Exercises
  • 6: Test Bank
  
  
• Chapter 7: Sampling Distributions
  • 7.1: Introduction
  • 7.2: Sampling Plans and Experimental Designs
  • 7.3: Statistics and Sampling Distributions
  • 7.4: The Central Limit Theorem
  • 7.5: The Sampling Distribution of the Sample Mean
  • 7.6: The Sampling Distribution of the Sample Proportion
  • 7.7: A Sampling Application: Statistical Process Control (Optional)
  • 7: Supplementary Exercises
  • 7: Test Bank
  
  
• Chapter 8: Large-Sample Estimation
  • 8.1: Where We've Been and Where We're Going
  • 8.2: Types of Estimators
  • 8.3: Point Estimation
  • 8.4: Interval Estimation
  • 8.5: Estimating the Difference between Two Population Means
  • 8.6: Estimating the Difference between Two Binomial Proportions
  • 8.7: One-Sided Confidence Bounds
  • 8.8: Choosing the Sample Size
  • 8: Supplementary Exercises
  • 8: Test Bank
  
  
• Chapter 9: Large-Sample Tests of Hypotheses
  • 9.1: Testing Hypotheses about Population Parameters
  • 9.2: A Statistical Test of Hypothesis
  • 9.3: A Large-Sample Test about a Population Mean
  • 9.4: A Large-Sample Test of Hypothesis for the Difference between Two Population Means
  • 9.5: A Large-Sample Test of Hypothesis for a Binomial Proportion
  • 9.6: A Large-Sample Test of Hypothesis for the Difference between Two Binomial Proportions
  • 9.7: Some Comments on Testing Hypotheses
  • 9: Supplementary Exercises
  • 9: Test Bank
  
  
• Chapter 10: Inference from Small Samples
  • 10.1: Introduction
  • 10.2: Student's t Distribution
  • 10.3: Small-Sample Inferences Concerning a Population Mean
  • 10.4: Small-Sample Inferences for the Difference between Two Population Means: Independent Random Samples
  • 10.5: Small-Sample Inferences for the Difference between Two Means: A Paired-Difference Test
  • 10.6: Inferences Concerning a Population Variance
  • 10.7: Comparing Two Population Variances
  • 10.8: Revisiting the Small-Sample Assumptions
  • 10: Supplementary Exercises
  • 10: Test Bank
  
  
• Chapter 11: The Analysis of Variance
  • 11.1: The Design of an Experiment
  • 11.2: What Is an Analysis of Variance?
  • 11.3: The Completely Randomized Design: A One-Way Classification
  • 11.4: Ranking Population Means
  • 11.5: The Randomized Block Design: A Two-Way Classification
  • 11.6: The Analysis of Variance for a Randomized Block Design
  • 11.7: The a × b Factorial Experiment: A Two-Way Classification
  • 11.8: The Analysis of Variance for an a × b Factorial Experiment
  • 11.9: Revisiting the Analysis of Variance Assumptions
  • 11.10: A Brief Summary
  • 11: Supplementary Exercises
  • 11: Test Bank
  
  
• Chapter 12: Linear Regression and Correlation
  • 12.1: Introduction
  • 12.2: A Simple Linear Probabilistic Model and Least Squares
  • 12.3: An Analysis of Variance for Linear Regression
  • 12.4: Testing the Usefulness of the Linear Regression Model
  • 12.5: Diagnostic Tools for Checking the Regression Assumptions
  • 12.6: Estimation and Prediction Using the Fitted Line
  • 12.7: Correlation Analysis
  • 12: Supplementary Exercises
  • 12: Test Bank
  
  
• Chapter 13: Multiple Regression Analysis
  • 13.1: Introduction
  • 13.2: The Multiple Regression Model
  • 13.3: A Multiple Regression Analysis
  • 13.4: A Polynomial Regression Model
  • 13.5: Using Quantitative and Qualitative Predictor Variables in a Regression Model
  • 13.6: Testing Sets of Regression Coefficients
  • 13.7: Interpreting Residual Plots
  • 13.8: Stepwise Regression Analysis
  • 13.9: Misinterpreting a Regression Analysis
  • 13.10: Steps to Follow When Building a Multiple Regression Model
  • 13: Supplementary Exercises
  • 13: Test Bank
  
  
• Chapter 14: Analysis of Categorical Data
  • 14.1: A Description of the Experiment
  • 14.2: Pearson's Chi-Square Statistic
  • 14.3: Testing Specified Cell Probabilities: The Goodness-of-Fit Test
  • 14.4: Contingency Tables: A Two-Way Classification
  • 14.5: Comparing Several Multinomial Populations: A Two-Way Classification with Fixed Row or Column Totals
  • 14.6: The Equivalence of Statistical Tests
  • 14.7: Other Applications of the Chi-Square Test
  • 14: Supplementary Exercises
  • 14: Test Bank
  
  
• Chapter 15: Nonparametric Statistics
  • 15.1: Introduction
  • 15.2: The Wilcoxon Rank Sum Test: Independent Random Samples
  • 15.3: The Sign Test for a Paired Experiment
  • 15.4: A Comparison of Statistical Tests
  • 15.5: The Wilcoxon Signed-Rank Test for a Paired Experiment
  • 15.6: The Kruskal–Wallis H Test for Completely Randomized Designs
  • 15.7: The Friedman F_r Test for Randomized Block Designs
  • 15.8: Rank Correlation Coefficient
  • 15.9: Summary
  • 15: Supplementary Exercises
  • 15: Test Bank