# OpenIntro Statistics 4th edition

David M. Diez, Mine Cetinkaya-Rundel, and Christopher D. Barr
Publisher: OpenIntro

## Textbook Resources

Additional instructional and learning resources are available with the textbook, and might include testbanks, slide presentations, online simulations, videos, and documents.

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

• Chapter 1: Introduction to data
• 1.1: Case study: using stents to prevent strokes (2)
• 1.2: Data basics (10)
• 1.3: Sampling principles and strategies (16)
• 1.4: Experiments (16)
• 1: Chapter exercises

• Chapter 2: Summarizing data
• 2.1: Examining numerical data (19)
• 2.2: Considering categorical data (4)
• 2.3: Case study: malaria vaccine (2)
• 2: Chapter exercises (8)
• 2: Labs (22)

• Chapter 3: Probability
• 3.1: Defining probability (12)
• 3.2: Conditional probability (10)
• 3.3: Sampling from a small population (6)
• 3.4: Random variables (8)
• 3.5: Continuous distributions (11)
• 3: Chapter exercises
• 3: Labs (10)

• Chapter 4: Distributions of random variables
• 4.1: Normal distribution (10)
• 4.2: Geometric distribution (6)
• 4.3: Binomial distribution (10)
• 4.4: Random variables (4)
• 4.5: Continuous distributions (18)
• 4: Chapter exercises
• 4: Labs (5)

• Chapter 5: Foundations for inference
• 5.1: Point estimates and sampling variability (7)
• 5.2: Confidence intervals for a proportion (8)
• 5.3: Hypothesis testing for a proportion (26)
• 5: Chapter exercises
• 5: Labs (6)

• Chapter 6: Inference for categorical data
• 6.1: Inference for a single proportion (15)
• 6.2: Difference of two proportions (14)
• 6.3: Testing for goodness of fit using chi-square (5)
• 6.4: Testing for independence in two-way tables (18)
• 6: Chapter exercises
• 6: Labs (24)

• Chapter 7: Inference for numerical data
• 7.1: One-sample means with the t-distribution (14)
• 7.2: Paired data (8)
• 7.3: Difference of two means (10)
• 7.4: Power calculations for a difference of means (2)
• 7.5: Comparing many means with ANOVA (24)
• 7: Chapter exercises
• 7: Labs (29)

• Chapter 8: Introduction to linear regression
• 8.1: Fitting a line, residuals, and correlation (16)
• 8.2: Least squares regression (10)
• 8.3: Types of outliers in linear regression (4)
• 8.4: Inference for linear regression (14)
• 8: Chapter exercises
• 8: Labs (6)

• Chapter 9: Multiple and logistic regression
• 9.1: Introduction to multiple regression (6)
• 9.2: Model selection (6)
• 9.3: Checking model assumptions using graphs (2)
• 9.4: Multiple regression case study: Mario Kart
• 9.5: Introduction to logistic regression (9)
• 9: Chapter exercises
• 9: Labs (5)

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

Cengage is proud to support the open source teaching community through our partnership with OpenIntro. OpenIntro Statistics, 4th edition, by David M. Diez, Mine Çetinkaya-Rundel, and Christopher D. Barr is a college-level textbook covering data basics, probability, distributions, inference for means and proportions, and regression, including multiple and the basics of logistic regression. The WebAssign component for this title features an eBook, class analytics tools, and instant student feedback on questions.

Features
• Every WebAssign question links to applicable chapters in a fully integrated eBook.
• Lecture videos created by OpenIntro that provide an overview of the content in each section.
• Over 300 end-of-section problems direct from the text suitable for homework, review, and tests.
• Labs (Lab) – Students can perform real statistical analysis in class or online with premade and module-specific Stats Labs. Require students to use the instructor-selected data analysis tool to analyze a real data set, pulling together knowledge learned from that module and previous material to facilitate whole-picture learning.
• Project Milestones (PJT) allow one place for students to ideate, collaborate, and submit a longer-term project. The four sequential milestones are:
1. Research Design
2. Gather Data
3. Analyze Data
4. Present Results
• Use the Textbook Edition Upgrade Tool to automatically update all of your assignments from the previous edition to corresponding questions in this textbook.

## 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
C - End of Chapter Exercise
PJT - Project Milestone

##### 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: Introduction to data
1.1 2 001 002
1.2 10 003 004 005 006 007 008 009 010 011 012
1.3 16 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028
1.4 16 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044
Chapter 2: Summarizing data
2.C 8 027 028 029 030 031 032 033 034
2.Lab 22 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 004.Excel 004.JMP 004.Minitab 004.R 004.SPSS
2.1 19 001 002 003 004 005 006 008 009 010 011 012 013 014 015 016 017 018 019 020
2.2 4 021 022 023 024
2.3 2 025 026
Chapter 3: Probability
3.Lab 10 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS
3.1 12 001 002 003 004 005 006 007 008 009 010 011 012
3.2 10 013 014 015 016 017 018 019 020 021 022
3.3 6 023 024 025 026 027 028
3.4 8 029 030 031 032 033 034 035 036
3.5 11 037 038 039 040 041 042 043 044 045 046 047
Chapter 4: Distributions of random variables
4.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
4.1 10 001 002 003 004 005 006 007 008 009 010
4.2 6 011 012 013 014 015 016
4.3 10 017 018 019 020 021 022 023 024 025 026
4.4 4 027 028 029 030
4.5 18 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048
Chapter 5: Foundations for inference
5.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
5.1 7 001 002 003 004 005 006 501.XP
5.2 8 007 008 009 010 011 012 013 014
5.3 26 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 501.XP 502.XP 503.XP
Chapter 6: Inference for categorical data
6.Lab 24 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 003.TI 004.Excel 004.JMP 004.Minitab 004.R 004.SPSS 004.TI
6.1 15 001 002 003 004 006 007 008 009 010 011 012 013 014 015 016
6.2 14 018 019 020 021 022 023 024 025 026 027 028 029 030 501.XP
6.3 5 031 032 033 034 501.XP
6.4 18 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 501.XP 502.XP
Chapter 7: Inference for numerical data
7.Lab 29 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI 003.Excel 003.JMP 003.Minitab 003.R 003.SPSS 003.TI 004.Excel 004.JMP 004.Minitab 004.R 004.SPSS 005.Excel 005.JMP 005.Minitab 005.R 005.SPSS 005.TI
7.1 14 001 002 003 004 005 006 007 008 009 010 011 012 013 014
7.2 8 015 016 017 018 019 020 021 022
7.3 10 023 024 025 026 027 028 029 030 031 032
7.4 2 033 034
7.5 24 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058
Chapter 8: Introduction to linear regression
8.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
8.1 16 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016
8.2 10 017 018 019 020 021 022 023 024 025 026
8.3 4 027 028 029 030
8.4 14 031 032 033 034 035 036 037 038 039 040 041 042 043 044
Chapter 9: Multiple and logistic regression
9.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
9.1 6 001 002 003 004 005 006
9.2 6 007 008 009 010 011 012
9.3 2 013 014
9.5 9 015 016 017 018 019 020 021 022 023
Total 501