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Mathematical Statistics with Applications 8th edition

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Dennis D. Wackerly, John Tuhao Chen, and Adam Loy
Publisher: Cengage Learning

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  • Wackerly Mathematical Statistics with Applications 8e
  • Wackerly Mathematical Statistics with Applications with R 8e

Access is contingent on use of this textbook in the instructor's classroom.

  • Chapter 1: What Is Statistics?
    • 1: Concept Explorations (2)
    • 1: Precalculus Review (10)
    • 1.1: Population and Data
    • 1.2: Characterizing a Set of Measurements: Graphical Methods (7)
    • 1.3: Characterizing a Set of Measurements: Numerical Methods (9)
    • 1.4: Making Statistical Inference
    • 1: Supplementary Exercises (8)

  • Chapter 2: Probability
    • 2: Concept Explorations (3)
    • 2: Precalculus Review (13)
    • 2.1: Interpreting Probabilities
    • 2.2: A Review of Set Notation (4)
    • 2.3: A Probabilistic Model for an Experiment: The Discrete Case (12)
    • 2.4: Calculating the Probability of an Event: The Sample-Point Method (8)
    • 2.5: Tools for Counting Sample Points (19)
    • 2.6: Conditional Probability and the Independence of Events (9)
    • 2.7: Two Laws of Probability (10)
    • 2.8: Calculating the Probability of an Event: The Event-Composition Method (6)
    • 2.9: The Law of Total Probability and Bayes' Rule (7)
    • 2: Supplementary Exercises (20)

  • Chapter 3: Discrete Random Variables and Their Probability Distributions
    • 3: Concept Explorations (1)
    • 3: Precalculus and Calculus Review (19)
    • 3.1: Random Variables (3)
    • 3.2: The Probability Distribution for a Discrete Random Variable (6)
    • 3.3: The Expected Value of a Random Variable or a Function of a Random Variable (13)
    • 3.4: The Bernoulli and Binomial Probability Distributions (22)
    • 3.5: The Geometric Probability Distribution (15)
    • 3.6: The Negative Binomial Probability Distribution (Optional) (8)
    • 3.7: The Hypergeometric Probability Distribution (13)
    • 3.8: The Poisson Probability Distribution (14)
    • 3.9: Moments and Moment-Generating Functions (10)
    • 3.10: Chebyshev's Inequality for Discrete Random Variables (6)
    • 3: Supplementary Exercises (19)

  • Chapter 4: Continuous Variables and Their Probability Distributions
    • 4: Concept Explorations (1)
    • 4: Calculus Review (15)
    • 4.1: The Probability Distribution for a Continuous Random Variable (4)
    • 4.2: Expected Values for Continuous Random Variables (13)
    • 4.3: The Uniform Probability Distribution (10)
    • 4.4: The Normal Probability Distribution (16)
    • 4.5: The Gamma Probability Distribution (19)
    • 4.6: The Beta Probability Distribution (10)
    • 4.7: Moments and Moment-Generating Functions for Continuous Random Variables (5)
    • 4.8: Chebyshev's Inequality for Continuous Random Variables (4)
    • 4.9: Expectations of Discontinuous Functions and Mixed Probability Distributions (Optional) (4)
    • 4: Supplementary Exercises (18)

  • Chapter 5: Multivariate Probability Distributions
    • 5: Concept Explorations (1)
    • 5: Precalculus and Calculus Review (11)
    • 5.1: Bivariate and Multivariate Probability Distributions (12)
    • 5.2: Marginal and Conditional Probability Distributions (13)
    • 5.3: Independent Random Variables (15)
    • 5.4: The Expected Value of a Function of Random Variables (10)
    • 5.5: The Covariance of Two Random Variables (7)
    • 5.6: The Expected Value and Variance of Linear Functions of Random Variables (8)
    • 5.7: The Multinomial Probability Distribution (7)
    • 5.8: The Bivariate Normal Distribution (Optional)
    • 5.9: Conditional Expectations (6)
    • 5: Supplementary Exercises (11)

  • Chapter 6: Functions of Random Variables
    • 6: Concept Explorations (1)
    • 6: Precalculus and Calculus Review (9)
    • 6.1: Transformations Using the Cumulative Distribution Function (11)
    • 6.2: Density Transformations via Change of Variables (7)
    • 6.3: Transformations of Moment-Generating Functions (12)
    • 6.4: Multivariate Transformations (Optional)
    • 6: Supplementary Exercises (11)

  • Chapter 7: Sampling Distributions
    • 7: Concept Explorations (1)
    • 7: Precalculus Review (13)
    • 7.1: Basic Sampling Statistics (1)
    • 7.2: Sampling Distributions Related to Normal Data (19)
    • 7.3: The Central Limit Theorem (15)
    • 7.4: A Proof of the Central Limit Theorem (Optional)
    • 7.5: The Normal Approximation to the Binomial Distribution (15)
    • 7.6: Order Statistics
    • 7: Supplementary Exercises (9)
    • 7: Labs (6)

  • Chapter 8: Estimation
    • 8: Concept Explorations (2)
    • 8: Precalculus and Calculus Review (15)
    • 8.1: The Bias and Mean Square Error of Point Estimators (8)
    • 8.2: Unbiased Point Estimators on Mean and Proportions (11)
    • 8.3: Confidence Intervals (6)
    • 8.4: Large-Sample Confidence Intervals (6)
    • 8.5: Selecting the Sample Size (4)
    • 8.6: Small-Sample Confidence Intervals for μ and μ1 − μ2 (14)
    • 8.7: Confidence Intervals for σ2 (7)
    • 8: Supplementary Exercises (13)

  • Chapter 9: Properties of Point Estimators
    • 9: Concept Explorations (1)
    • 9: Precalculus and Calculus Review (9)
    • 9.1: Relative Efficiency (3)
    • 9.2: Consistency (12)
    • 9.3: Sufficiency (10)
    • 9.4: Uniformly Minimum Variance Unbiased Estimators (6)
    • 9.5: The Method of Moments (6)
    • 9.6: The Method of Maximum Likelihood (10)
    • 9.7: Large-Sample Confidence Intervals Based on Maximum-Likelihood Estimators (Optional) (2)
    • 9: Supplementary Exercises (5)

  • Chapter 10: Hypothesis Testing
    • 10: Concept Explorations (2)
    • 10: Precalculus Review (6)
    • 10.1: Elements of a Statistical Test (5)
    • 10.2: Common Large-Sample Tests (6)
    • 10.3: Calculating Type II Error Probabilities and Finding the Sample Size for Z Tests (11)
    • 10.4: Relationships Between Hypothesis-Testing Procedures and Confidence Intervals (3)
    • 10.5: Another Way to Report the Results of a Statistical Test: p-Values (4)
    • 10.6: Some Comments on the Theory of Hypothesis Testing (1)
    • 10.7: Small-Sample Hypothesis Testing for μ and μ1 − μ2 (7)
    • 10.8: Testing Hypotheses Concerning Variances (9)
    • 10.9: Power of Tests and the Neyman–Pearson Lemma (9)
    • 10.10: Likelihood Ratio Tests (3)
    • 10: Supplementary Exercises (8)

  • Chapter 11: Linear Models and Estimation by Least Squares
    • 11: Concept Explorations (2)
    • 11: Precalculus and Calculus Review (16)
    • 11.1: Linear Statistical Models
    • 11.2: The Method of Least Squares (3)
    • 11.3: Properties of the Least-Squares Estimators: Simple Linear Regression (10)
    • 11.4: Inferences Concerning the Parameters βi (7)
    • 11.5: Inferences Concerning Linear Functions of the Model Parameters: Simple Linear Regression (5)
    • 11.6: Predicting a Particular Value of Y by Using Simple Linear Regression (3)
    • 11.7: Checking Model Assumptions (4)
    • 11.8: Correlation (4)
    • 11.9: Transformations (4)
    • 11.10: Fitting the Linear Model by Using Matrices (3)
    • 11.11: Linear Functions of the Model Parameters: Multiple Linear Regression
    • 11.12: Inferences Concerning Linear Functions of the Model Parameters: Multiple Linear Regression (4)
    • 11.13: Predicting a Particular Value of Y by Using Multiple Regression (4)
    • 11.14: A Test for H0 : βg + 1 = βg + 2 = … = βk = 0 (9)
    • 11: Supplementary Exercises (6)

  • Chapter 12: Experimental Designs
    • 12: Concept Explorations (1)
    • 12: Precalculus Review (7)
    • 12.1: Sampling Information
    • 12.2: Designing Experiments to Increase Accuracy (4)
    • 12.3: The Matched-Pairs Experiment (7)
    • 12.4: Some Elementary Experimental Designs (6)
    • 12: Supplementary Exercises (5)

  • Chapter 13: The Analysis of Variance
    • 13: Concept Explorations (1)
    • 13: Precalculus Review (10)
    • 13.1: ANOVA to Compare Two Means (4)
    • 13.2: ANOVA for Three or More Means (5)
    • 13.3: A Statistical Model for the One-Way Layout (2)
    • 13.4: Estimation in the One-Way Layout (11)
    • 13.5: A Statistical Model for the Randomized Block Design (2)
    • 13.6: The Analysis of Variance for a Randomized Block Design (6)
    • 13.7: Estimation in the Randomized Block Design (5)
    • 13.8: Selecting the Sample Size (1)
    • 13.9: Simultaneous Confidence Intervals Using the Bonferroni Adjustment (3)
    • 13.10: Analysis of Variance Using Linear Models (3)
    • 13: Supplementary Exercises (11)
    • 13: Labs (5)

  • Chapter 14: Analysis of Categorical Data
    • 14: Concept Explorations (1)
    • 14: Precalculus and Calculus Review (10)
    • 14.1: The Chi-Square Test (6)
    • 14.2: Chi-Square Test of Independence (3)
    • 14.3: Chi-Square Test of Homogeneity (3)
    • 14.4: Permutation Tests for Small Counts (3)
    • 14: Supplementary Exercises (6)

  • Chapter 15: Nonparametric Statistics
    • 15: Concept Explorations (1)
    • 15: Precalculus Review (7)
    • 15.1: The Sign Test for a Matched-Pairs Experiment (6)
    • 15.2: The Wilcoxon Signed-Rank Test for a Matched-Pairs Experiment (6)
    • 15.3: The Wilcoxon–Mann–Whitney Test Comparing Two Independent Samples (4)
    • 15.4: The Kruskal–Wallis Test for the One-Way Layout (5)
    • 15.5: The Friedman Test for Randomized Block Designs (5)
    • 15.6: The Runs Test: A Test for Randomness (4)
    • 15.7: Rank Correlation Coefficient (5)
    • 15: Supplementary Exercises (9)

  • Chapter 16: Introduction to Bayesian Methods for Inference
    • 16: Concept Explorations
    • 16: Precalculus and Calculus Review (5)
    • 16.1: Bayesian Priors, Posteriors, and Estimators (6)
    • 16.2: Bayesian Credible Intervals (6)
    • 16.3: Bayesian Tests of Hypotheses (5)

  • Chapter PJT: Project
    • PJT.1: Project (4)


Wackerly/Chen/Loy’s Mathematical Statistics with Applications, 8th Edition, with WebAssign, builds a solid foundation in statistical theory while conveying its relevance in solving practical problems in the real world. Students discover the nature of statistics and understand its essential role in scientific research. The focused approach emphasizes the connectivity of key concepts with statistical inference being the primary theme. Updated to engage all students, the new edition includes enhanced insights and cutting-edge knowledge on theory and applications of statistics today. It preserves the elegance of the previous edition, while embracing new methodologies in data science, statistical learning and biostatistics.

Instructor Product Features

  • Instructor Resources include Instructional Lecture Videos, hosted by Dana Mosely. These topic-specific videos provide explanations of key concepts, examples, and applications in a lecture-based format. Image Library PowerPoint slides are also available.

Student Learning Tools

  • Read It links under each question quickly jump to the corresponding section of a complete, interactive eTextbook that lets students highlight and take notes as they read.
  • Student Resources include Data Analysis Tool Instructions / Tech Guides for the below software. Can be used stand-alone or in conjunction with assessment items (Homework, Labs, or Project Milestones).
    • TI-83/84 and TI-Nspire Calculator
    • Excel
    • JMP
    • Minitab
    • SPSS
    • R
  • Precalculus and Calculus Review is available within each chapter to assign to help close readiness gaps.

Content Available for Statistics

  • View several of the often-available question types in Statistics content here. You can see which questions are available for your specific course below.

Questions Available within WebAssign

Most questions from this textbook are available in WebAssign. The online questions are identical to the textbook questions except for minor wording changes necessary for Web use. Whenever possible, variables, numbers, or words have been randomized so that each student receives a unique version of the question. This list is updated nightly.

Question Group Key
E - End of Section Exercise
SIP - Stats in Practice Video Question
Lab - Lab
P - Precalculus/Calculus Prerequisite Exercise
PJT - Project Milestone
CE - Concept Explorations
AQ - Applet Question
R - R Question
SE - Supplemental Exercise
XP - Extra Problem


Question Availability Color Key
BLACK questions are available now
GRAY questions are under development


Group Quantity Questions
Chapter PJT: Project
PJT.1 4 001 002 003 004
Chapter 1: What Is Statistics?
1.CE 2 001.SIP 002.SIP
1.P 10 001 002 003 004 005 006 007 008 009 010
1.SE 8 027 029 031 033 035 037 501.XP 502.XP
1.2 7 004.R 005 006 007 008.R 501.XP 502.XP
1.3 9 011 013 014.R 015 017 019 021 501.XP 502.XP
Chapter 2: Probability
2.CE 3 001.SIP 002.SIP 003.SIP
2.P 13 001 002 003 004 005 006 007 008 009 010 011 012 013
2.SE 20 163 165 167 170 172 174 178 180 182 184 186 188 190 194 196 198 200 202 501.XP 502.XP
2.2 4 005 008 011 501.XP
2.3 12 013 016 022 024 026 028 029 031 033 036 038 501.XP
2.4 8 040 042 044 046 501.XP 502.XP 503.XP 504.XP
2.5 19 050 052 058 059 063 065 067 069 071 075 080 081 083 087 089 091 501.XP 502.XP 503.XP
2.6 9 095 097 098.R 099 102 104 106 108 501.XP
2.7 10 114 117 118.R 121 123 124 125 126 127 129
2.8 6 131 133 135 138 140 142
2.9 7 149 154.R 155 157 159 161 501.XP
Chapter 3: Discrete Random Variables and Their Probability Distributions
3.CE 1 001.SIP
3.P 19 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019
3.SE 19 226 228 230 232 234 236 238 240 242 246 248 250 252 254 256 258 260 262 501.XP
3.1 3 501.XP 502.XP 503.XP
3.2 6 007 009 011 013 015 017
3.3 13 027 028.R 031 033 035 037 039 043 045 047 048.R 501.XP 502.XP
3.4 22 053 060 061 062 066.AQ 066.R 067 075 076.R 077 079 083 084.R 085 087 089 501.XP 502.XP 503.XP.R 504.XP 505.XP 506.XP
3.5 15 091 098.R 099 100.R 101 103 105 106.R 109 111 113 115 117 501.XP 502.XP
3.6 8 119 121 122 124 125.R 126 130 501.XP
3.7 13 134.R 135 137 139 141 142.R 143 147 150 152 501.XP.R 502.XP 503.XP.R
3.8 14 159 161.R 162 164 166 168 169 170 172 176 178 182 185 187
3.9 10 190 192 194 196 198 200 202 204 206 208
3.10 6 212 214 216 218 222 224
Chapter 4: Continuous Variables and Their Probability Distributions
4.CE 1 001.SIP
4.P 15 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
4.SE 18 176 178 180 182 186 188 190 192 194 196 198 200 202 204 206 208 214 501.XP
4.1 4 003 007 009 011
4.2 13 017 019 021 027 029 031 033 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP
4.3 10 038 041 045 046.R 049 051 053 055 501.XP 502.XP
4.4 15 060 062 064 068 069-071.AQ 072 074 075.R 076 501.XP 502.XP 503.XP 504.XP.R 505.XP 506.XP
4.5 19 083 086.AQ 091.AQ 094 096 097.R 098 100 102 104 106 107.R 108 110 111.R 112 114 501.XP 502.XP
4.6 10 121.AQ 127 128.AQ 129 131 132.R 133 135 137 139
4.7 5 148 150 152 154 156
4.8 4 161 163 165 167
4.9 4 169 172 173 501.XP
Chapter 5: Multivariate Probability Distributions
5.CE 1 001.SIP
5.P 11 001 002 003 004 005 006 007 008 009 010 011
5.SE 11 180 182 184 186 188 190 192 193 196 200 201
5.1 12 001 007 009 010.R 011 013 015.R 016 018 020 501.XP 502.XP
5.2 13 022 024 027 029 031 033 034.R 035 037 039 041 043 045
5.3 15 050 052 055 057 059 061 065 067 069 071 073 075 081 083 503.XP
5.4 10 084 085 088.R 089 091 093 095 097 099 501.XP
5.5 7 101 103 105 107 109 111 113
5.6 8 120 125 127 129 131 133 135 501.XP
5.7 7 137 139 141 143 144 145 501.XP.R
5.9 6 165 167 169 171 173 175
Chapter 6: Functions of Random Variables
6.CE 1 001.SIP
6.P 9 001 002 003 004 005 006 007 008 009
6.SE 11 094 096 098 100 102 104 106 108 110 112 116
6.1 11 001 003 005 007 009 011 013 015 017 019 021
6.2 7 023 025 026 029 031 033 035
6.3 12 037 039 041 043 045 047 049 051 055 057 059 061
Chapter 7: Sampling Distributions
7.CE 1 001.SIP
7.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
7.P 13 001 002 003 004 005 006 007 008 009 010 011 012 013
7.SE 9 105 107 109 111 113 115 117 119 121
7.1 1 002.AQ
7.2 19 007 009 011 013 014 015.R 016.AQ 016.R 017 019 021.R 022.AQ 024.AQ 028 030 032 034 036 501.XP.R
7.3 15 039 043.R 044 046 048 049.R 050 051.R 052 054 056 058 060 501.XP 503.XP
7.5 15 063 067 068.R 069 071 073 075 079 081 083 502.XP 503.XP.AQ 504.XP.R 505.XP 506.XP.R
Chapter 8: Estimation
8.CE 2 001.SIP 002.SIP
8.P 15 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
8.SE 13 104 105 107 109 111 113 115 117 119 121 125 126 501.XP
8.1 8 005 007 009 011 013 015 017 019
8.2 11 023 025 027 028.R 031 033 035 037 501.XP 502.XP 503.XP
8.3 6 039 041 043 045 047 049
8.4 6 061 065 066.R 067 501.XP 502.XP
8.5 4 072.R 075 077 079
8.6 14 081 085 087 088 089 091 093 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP 507.XP
8.7 7 096.R 099 100.R 101 103 501.XP 502.XP
Chapter 9: Properties of Point Estimators
9.CE 1 001.SIP
9.P 9 001 002 003 004 005 006 007 008 009
9.SE 5 103 105 107 109 111
9.1 3 005 007 501.XP
9.2 12 015 023 025 027 029 031 033 035 501.XP 502.XP 503.XP 504.XP
9.3 10 041 043 045 047 049 051 053 055 501.XP 502.XP
9.4 6 056 057 059 061 065 067
9.5 6 070 071 073 075 077 079
9.6 10 081 085 087 089 091 093 095 097 501.XP 502.XP
9.7 2 099 101
Chapter 10: Hypothesis Testing
10.CE 2 001.SIP 002.SIP
10.P 6 001 002 003 004 005 006
10.SE 8 123 125 127 129 131 135 137 501.XP
10.1 5 002 003 005 006 007
10.2 6 019 020.R 021 031 033 501.XP.R
10.3 11 043 501.XP 502.XP 503.XP.R 504.XP 505.XP 506.XP.R 507.XP 508.XP 509.XP 510.XP
10.4 3 046 501.XP 502.XP
10.5 4 051.R 052 053.R 058
10.6 1 501.XP
10.7 7 069 501.XP 502.XP.R 503.XP 504.XP.R 505.XP.R 506.XP
10.8 9 086.R 089 093 095 501.XP 502.XP 503.XP 504.XP 505.XP
10.9 9 099 101 103 105 107 109 111 501.XP 502.XP.R
10.10 3 113 115 117
Chapter 11: Linear Models and Estimation by Least Squares
11.CE 2 001.SIP 002.SIP
11.P 16 001 002 003 004 005 006 007 008 009 011 012 013 014 015 016 017
11.SE 6 119 121 123 125 127 129
11.2 3 004 006 008.AQ
11.3 10 020 501.XP 502.XP.AQ 503.XP 504.XP 505.XP.R 506.XP 507.XP.R 508.XP 509.XP
11.4 7 030 032 034 501.XP.R 502.XP.R 503.XP 504.XP
11.5 5 035 042 501.XP 502.XP.R 503.XP
11.6 3 501.XP 502.XP 503.XP.R
11.7 4 501.XP 502.XP 503.XP.R 504.XP
11.8 4 068 070 072 501.XP
11.9 4 076 078 501.XP 502.XP.R
11.10 3 083 084.R 501.XP
11.12 4 095 097 099 100.R
11.13 4 101 103 501.XP.R 502.XP
11.14 9 105 106.R 107 109 111 115 117 501.XP 502.XP
Chapter 12: Experimental Designs
12.CE 1 001.SIP
12.P 7 001 002 003 004 005 006 007
12.SE 5 034 036 038 040 042
12.2 4 006 008 010 012
12.3 7 014 015.R 016 019.R 022 501.XP 502.XP
12.4 6 024 030 032 501.XP 502.XP 503.XP
Chapter 13: The Analysis of Variance
13.CE 1 001.SIP
13.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
13.P 10 001 002 003 004 005 006 007 008 009 010
13.SE 11 077 079 081 083 085 087 089 093 095 097 501.XP
13.1 4 001 001.R 501.XP.R 502.XP
13.2 5 004 006 008 010 011.R
13.3 2 018 020
13.4 11 025 027 028.R 031 034.R 035 037 039 501.XP.R 502.XP 503.XP
13.5 2 041 043
13.6 6 045 047 051 053 055 501.XP.R
13.7 5 056.R 057 061 501.XP 502.XP
13.8 1 063
13.9 3 067 072.R 501.XP
13.10 3 073 074.R 075
Chapter 14: Analysis of Categorical Data
14.CE 1 001.SIP
14.P 10 001 002 003 004 005 006 007 008 009 010
14.SE 6 045 049 051 053 055 501.XP
14.1 6 005 007 009 017 501.XP 502.XP.R
14.2 3 021 024.R 028
14.3 3 031 037 039
14.4 4 501.XP 502.XP 503.XP 504.XP.R
Chapter 15: Nonparametric Statistics
15.CE 1 001.SIP
15.P 7 001 002 003 004 005 006 007
15.SE 9 063 065 067 069 071 073 075 077 501.XP
15.1 6 003 004.R 005 007 009 501.XP
15.2 6 011 013 015 016.R 017 019
15.3 4 021 023 024.R 025
15.4 5 029 030.R 031 033 035
15.5 5 039 040.R 043 045 501.XP
15.6 4 047 049 051 502.XP
15.7 5 053 055 056.R 057 059
Chapter 16: Introduction to Bayesian Methods for Inference
16.P 5 001 002 003 004 005
16.1 6 003 009 011 012 013 015
16.2 6 021 023 024.R 025 026.R 501.XP
16.3 5 029 031 032.R 033 034.R
Total 1163  

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