# Statistics: Learning from Data (Updated AP Edition) 2nd edition

Roxy Peck, Tom Short, and Chris Olsen
Publisher: Cengage Learning

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• Peck Statistics: Learning From Data (Updated AP® Edition) 2e with SALT
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• Peck Statistics: Learning From Data (Updated AP® Edition) 2e: FT5 AP® Review and Practice Tests

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• Chapter 1: Graphical Methods for Describing Data Distributions
• 1: Concept Explorations (3)
• 1.1: Statistics—It's All About Variability
• 1.2: Selecting an Appropriate Graphical Display (10)
• 1.3: Displaying Categorical Data: Bar Charts and Comparative Bar Charts (6)
• 1.4: Displaying Numerical Data: Dotplots, Stem-and-Leaf Displays, and Histograms (17)
• 1.5: Graphical Displays in the Media (5)
• 1.6: Avoid These Common Mistakes
• 1: Review Exercises (8)
• 1: JMP Simulations (8)

• Chapter 2: Numerical Methods for Describing Data Distributions
• 2: Concept Explorations (3)
• 2.1: Selecting Appropriate Numerical Summaries (8)
• 2.2: Describing Center and Variability for Data Distributions That Are Approximately Symmetric (12)
• 2.3: Describing Center and Variability for Data Distributions That Are Skewed or Have Outliers (11)
• 2.4: Summarizing a Data Set: Boxplots (11)
• 2.5: Measures of Relative Standing: z-scores and Percentiles (14)
• 2.6: Avoid These Common Mistakes
• 2: Review Exercises (10)
• 2: AP® Review Questions (32)
• 2: JMP Simulations (16)

• Chapter 3: Describing Bivariate Data
• 3: Concept Explorations (2)
• 3.1: Describing Bivariate Categorical Data: Relative Frequency Tables and Mosaic Plots (3)
• 3.2: Displaying Bivariate Numerical Data: Scatterplots and Time Series Plots (7)
• 3.3: Correlation (12)
• 3.4: Linear Regression: Fitting a Line to Bivariate Data (11)
• 3.5: Assessing the Fit of a Line (13)
• 3.6: Describing Linear Relationships and Making Predictions—Putting It All Together
• 3.7: Modeling Nonlinear Relationships (7)
• 3.8: Avoid These Common Mistakes
• 3: Review Exercises (11)
• 3: AP® Review Questions (22)
• 3: JMP Simulations (15)

• Chapter 4: Collecting Data In Reasonable Ways
• 4: Concept Explorations (1)
• 4.1: Statistical Studies: Observation and Experimentation (9)
• 4.2: Collecting Data: Planning an Observational Study (12)
• 4.3: Collecting Data—Planning an Experiment (18)
• 4.4: The Importance of Random Selection and Random Assignment: What Types of Conclusions are Reasonable? (8)
• 4.5: Avoid These Common Mistakes
• 4: Review Exercises (9)
• 4: AP® Review Questions (16)
• 4: JMP Simulations

• Chapter 5: Probability
• 5: Concept Explorations (1)
• 5.1: Interpreting Probabilities (8)
• 5.2: Calculating Probabilities (8)
• 5.3: Probabilities of More Complex Events: Unions, Intersections, and Complements (15)
• 5.4: Conditional Probability (10)
• 5.5: Calculating Probabilities—A More Formal Approach (12)
• 5.6: Probability as a Basis for Making Decisions (1)
• 5.7: Estimating Probabilities Empirically and Using Simulation (5)
• 5: Review Exercises (10)

• Chapter 6: Random Variables and Probability Distributions
• 6: Concept Explorations (2)
• 6.1: Random Variables (7)
• 6.2: Probability Distributions for Discrete Random Variables (8)
• 6.3: Probability Distributions for Continuous Random Variables (13)
• 6.4: The Mean and Standard Deviation of a Random Variable (11)
• 6.5: Normal Distributions (21)
• 6.6: Checking for Normality (5)
• 6.7: Binomial and Geometric Distributions (19)
• 6.8: Using the Normal Distribution to Approximate a Discrete Distribution (Optional) (7)
• 6: Review Exercises (10)
• 6: AP® Review Questions (34)

• Chapter 7: Sampling Variability and Sampling Distributions
• 7: Concept Explorations (1)
• 7.1: Statistics and Sampling Variability (7)
• 7.2: The Sampling Distribution of a Sample Proportion (9)
• 7.3: The Sampling Distribution of the Sample Mean (14)
• 7.4: The Sampling Distribution of Differences in Sample Proportions or Sample Means (2)
• 7: Review Exercises (7)
• 7: AP® Review Questions (28)

• Chapter 8: An Overview of Statistical Inference—Learning from Data
• 8: Concept Explorations (1)
• 8.1: Statistical Inference—What You Can Learn From Data (8)
• 8.2: Selecting an Appropriate Method—Four Key Questions (11)
• 8.3: A Five-Step Process for Statistical Inference
• 8.4: How Sampling Distributions Support Learning From Data (8)
• 8: Review Exercises (9)

• Chapter 9: Estimating a Population Proportion
• 9: Concept Explorations (2)
• 9.1: Selecting an Estimator (9)
• 9.2: Estimating a Population Proportion—Margin of Error (13)
• 9.3: A Large Sample Confidence Interval for a Population Proportion (23)
• 9.4: Choosing a Sample Size to Achieve a Desired Margin of Error (6)
• 9.5: Avoid These Common Mistakes
• 9: Review Exercises (8)

• Chapter 10: Asking and Answering Questions About a Population Proportion
• 10: Concept Explorations (2)
• 10.1: Hypotheses and Possible Conclusions (10)
• 10.2: Potential Errors in Hypothesis Testing (9)
• 10.3: The Logic of Hypothesis Testing—An Informal Example (5)
• 10.4: A Procedure for Carrying Out a Hypothesis Test (6)
• 10.5: Large-Sample Hypothesis Tests for a Population Proportion (21)
• 10.6: Power and the Probability of Type II Error (8)
• 10.7: Avoid These Common Mistakes
• 10: Review Exercises (11)

• Chapter 11: Asking and Answering Questions About the Difference Between Two Population Proportions
• 11: Concept Explorations (1)
• 11.1: Estimating the Difference Between Two Population Proportions (10)
• 11.2: Testing Hypotheses About the Difference Between Two Population Proportions (5)
• 11.3: Inference for Two Proportions Using Data from an Experiment (8)
• 11.4: Avoid These Common Mistakes
• 11: Review Exercises (4)
• 11: AP® Review Questions (45)

• Chapter 12: Asking and Answering Questions About a Population Mean
• 12.1: A Confidence Interval for a Population Mean (19)
• 12.2: Testing Hypotheses About a Population Mean (15)
• 12.3: Avoid These Common Mistakes
• 12: Review Exercises (7)
• 12: JMP Simulations (22)

• Chapter 13: Asking and Answering Questions About the Difference Between Two Means
• 13: Concept Explorations (1)
• 13.1: Two Samples: Paired versus Independent Samples (2)
• 13.2: Learning About a Difference in Population Means Using Paired Samples (21)
• 13.3: Learning About a Difference in Population Means Using Independent Samples (24)
• 13.4: Inference for Two Means Using Data from an Experiment (20)
• 13.5: Avoid These Common Mistakes
• 13: Review Exercises (11)
• 13: AP® Review Questions (40)
• 13: JMP Simulations (20)

• Chapter 14: Learning from Categorical Data
• 14: Concept Explorations (1)
• 14.1: Chi-Square Tests for Univariate Categorical Data (16)
• 14.2: Tests for Homogeneity and Independence in a Two-Way Table (14)
• 14.3: Avoid These Common Mistakes
• 14: Review Exercises (7)
• 14: AP® Review Questions (17)
• 14: JMP Simulations (6)

• Chapter 15: Understanding Relationships—Numerical Data
• 15.1: The Simple Linear Regression Model (11)
• 15.2: Inferences Concerning the Slope of the Population Regression Line (11)
• 15.3: Checking Model Adequacy (11)
• 15: Review Exercises (4)
• 15: AP® Review Questions (17)

• Chapter FT5: Fast Track to a 5: Preparing for the AP® Statistics Examination
• FT5.DT: A Diagnostic Test (44)
• FT5.1: Exploring One-Variable Data (33)
• FT5.2: Exploring Two-Variable Data (17)
• FT5.3: Collecting Data Sensibly (17)
• FT5.4: Probability, Random Variables, and Probability Distributions (34)
• FT5.5: Sampling Distributions (17)
• FT5.6: Inferences for Categorical Data: Proportions (22)
• FT5.7: Inferences for Quantitative Data: Means (28)
• FT5.8: Inferences for Categorical Data: Chi-Square (17)
• FT5.9: Inferences for Quantitative Data: Slope (17)
• FT5.T1: Practice Test I (45)
• FT5.T2: Practice Test II (45)

Statistics: Learning From Data (AP® Edition), 2nd edition Updated, by Roxy Peck and Tom Short, addresses common problems faced by students and instructors with an innovative approach to elementary statistics. In this updated edition, early chapters have been reordered to match the AP® Statistics Course and Exam Description. Chapters have been grouped into nine units to match the course description. The organization by Learning Objective, focus on real-data examples, and adherence to the Guidelines for Assessment and Instruction in Statistics Education (GAISE), help students learn to think like statisticians. The AP® edition includes exam tips throughout the text along with sections designated to address common errors on the AP® exam.

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• #### Instructor Introduction - Statistical Analysis and Learning Tool (SALT) | WebAssign

The Statistical Analysis and Learning Tool (SALT) is designed by statisticians, for statisticians, to help you get introductory students deeply engaged in da...

Learn more about SALT at www.webassign.com/salt.
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• AP® Exam Practice (AP) questions at the end of each chapter help prepare students for the AP® Statistics exam.
• The Fast Track to a Five (FT5) AP® test preparation guide includes strategies for taking the exam, a diagnostic test so that students can assess their level of preparedness, chapter-review sections with self-study questions in AP® format, and two complete practice tests in AP® format.
• 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
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• R

### Questions to Help Students Gain Interest and Assess Conceptual Understanding

• Concept Video Questions (CV) provide students with a concept video along with two to three comprehension questions.
• Select Your Scenario (SYS) problems provide students with 3 different contexts to choose from. They select the scenario most relevant to them, and then solve the problem. Regardless of which scenario the student chooses, they will be required to answer questions demonstrating knowledge of a learning objective, making them the perfect questions to assign toward the end of a chapter.

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• The Statistical Analysis and Learning Tool (SALT) is designed by statisticians, for statisticians, to help you get introductory students deeply engaged in data manipulation, analysis, and interpretation without getting bogged down in complex computations.
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## 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 Availability Color Key
BLACK questions are available now
GRAY questions are under development

Group Quantity Questions
Chapter FT5: Fast Track to a 5: Preparing for the AP® Statistics Examination
FT5.DT 44 FR.001 FR.002 FR.003 FR.004 FR.005 FR.006 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022-024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040
FT5.T1 45 FR.001 FR.002 FR.003 FR.004 FR.005 FR.006 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040
FT5.T2 45 FR.001 FR.002 FR.003 FR.004 FR.005 FR.006 001 002 003 004 005 006 007 008 009 010 011 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040
FT5.1 33 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029
FT5.2 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
FT5.3 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
FT5.4 34 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030
FT5.5 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
FT5.6 22 FR.001 FR.002 FR.003 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019
FT5.7 28 FR.001 FR.002 FR.003 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025
FT5.8 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
FT5.9 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
Chapter 1: Graphical Methods for Describing Data Distributions
1.CE 3 001.CV 002.CV 003.CV
1.JMP 8 001 002 003 004 005 006 007 008
1.R 8 SYS.001.S 055 056 058 060 061 062 065
1.2 10 001 002 003 005 007 009 010 011 012 014
1.3 6 016.MI.S 016.MI.SA 017 018.MI.S 018.MI.SA 020.S
1.4 17 ST.001.S 024.MI.S 024.MI.SA 025.S 026 027 028 030 031.MI 031.MI.SA 032 037 038 039 040 044 045
1.5 5 046 047.S 049 051 052
Chapter 2: Numerical Methods for Describing Data Distributions
2.AP 32 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028
2.CE 3 001.CV 002.CV 003.CV
2.JMP 16 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016
2.R 10 SYS.001.S SYS.002.S 062.S 063.S 064.S 065.S 067.S 068.S 069.S 071
2.1 8 001.MI.S 001.MI.SA 003.S 004.S 005.S 007 010 011.S
2.2 12 ST.001.S ST.002.S 012.MI.S 012.MI.SA 013.MI.S 013.MI.SA 014.S 015 017.MI.S 017.MI.SA 018.S 021
2.3 11 025.S 026.MI.S 026.MI.SA 028.S 029.S 030.MI.S 030.MI.SA 031.MI.S 031.MI.SA 032.S 033
2.4 11 ST.001.S 035.S 036.S 037.S 039.S 041.MI.S 041.MI.SA 043.S 044 045 048.S
2.5 14 ST.001.S ST.002.S 050.MI 050.MI.SA 051 054 055.MI 055.MI.SA 057.S 058.MI 058.MI.SA 059.MI 059.MI.SA 061
Chapter 3: Describing Bivariate Data
3.AP 22 FR.001 FR.002 FR.003 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019
3.CE 2 001.CV 002.CV
3.JMP 15 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
3.R 11 079 080 082.S 084.S 089.S 090 091.S 092.S 093 095 096.S
3.1 3 001 003 005
3.2 7 007.S 008 009.S 010 012.MI 012.MI.SA 014
3.3 12 016 018 019.S 020.S 024 025 028.S 029.S 032.MI 032.MI.SA 034.MI 034.MI.SA
3.4 11 036 037 039.S 040.MI.S 040.MI.SA 044.S 046.MI.S 046.MI.SA 047.S 051 052
3.5 13 054.S 057.MI.S 057.MI.SA 059.S 060.S 061.MI.S 061.MI.SA 064 066 068.S 069.MI.S 069.MI.SA 071
3.7 7 072 073 074 075 076 077 078
Chapter 4: Collecting Data In Reasonable Ways
4.AP 16 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014
4.CE 1 001.CV
4.R 9 074 076 079 080 082 083 084 088 090
4.1 9 002 003 004 006 007 008 010 012 013
4.2 12 015 018 019 020 021 023 025 026 027 028 030 033
4.3 18 035 036 037 039 041 042 044 045 046 047 049 050 051 053 054 056 057 058
4.4 8 059 060 063 069 070 071 072 073
Chapter 5: Probability
5.CE 1 001.CV
5.R 10 082 083 085 087 088 091 094 095 098 099
5.1 8 001 003.MI 003.MI.SA 006.MI 006.MI.SA 008 009.MI 009.MI.SA
5.2 8 011 012 014 018.MI 018.MI.SA 019 020.MI 020.MI.SA
5.3 15 022 024.MI 024.MI.SA 025 026 028 032 034.MI 034.MI.SA 036 037.MI 037.MI.SA 038.MI 038.MI.SA 041
5.4 10 043 045 046 048 050.MI 050.MI.SA 052 053.MI 053.MI.SA 055
5.5 12 057 058 059 060.MI 060.MI.SA 062 063 064.MI 064.MI.SA 067.MI 067.MI.SA 068
5.6 1 071
5.7 5 072.MI 072.MI.SA 073 074 076
Chapter 6: Random Variables and Probability Distributions
6.AP 34 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030
6.CE 2 001.CV 002.CV
6.R 10 SYS.001.S 105 107 109 110 112 113.S 115.S 118.S 119
6.1 7 001 003 004 006 008.MI 008.MI.SA 009
6.2 8 010 011 013 015 018.MI 018.MI.SA 019.MI 019.MI.SA
6.3 13 021.MI 021.MI.SA 022 023.MI 023.MI.SA 024 025 026 027.MI 027.MI.SA 028 030.MI 030.MI.SA
6.4 11 032 033 035 036 038.MI 038.MI.SA 040 041 042 044.MI 044.MI.SA
6.5 21 ST.001.S ST.002.S SYS.002.S 045.MI.S 045.MI.SA 046.S 048.S 049.S 051.MI.S 051.MI.SA 052.S 054.MI.S 054.MI.SA 055 058.MI.S 058.MI.SA 059 064.MI.S 064.MI.SA 065.S 067.S
6.6 5 073 074.S 075.MI.S 075.MI.SA 076.S
6.7 19 ST.002.S SYS.002.S 078 079.MI.S 079.MI.SA 081.S 082 084.S 085.MI.S 085.MI.SA 087 088 089.MI 089.MI.SA 091.S 092 094.MI.S 094.MI.SA 095
6.8 7 097.MI 097.MI.SA 098 099.MI.S 099.MI.SA 100.S 102.S
Chapter 7: Sampling Variability and Sampling Distributions
7.AP 28 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024
7.CE 1 001.CV
7.R 7 051 052 055 059 060 061.S 062
7.1 7 001 002 003 007 010 013 014
7.2 9 016 017 019.MI 019.MI.SA 022 023 025.MI 025.MI.SA 028
7.3 14 029.MI 029.MI.SA 031 033 034.MI 034.MI.SA 035 036 038.MI.S 038.MI.SA.S 042.MI.S 042.MI.SA.S 044.S 046.S
7.4 2 047 049
Chapter 8: An Overview of Statistical Inference—Learning from Data
8.CE 1 001.CV
8.R 9 042 043 044 046 047 049 051 053 055
8.1 8 002 003 004 006 008 009 011 012
8.2 11 016 017 019 022 023 024 025 026 027 028 029
8.4 8 030 031 032.S 034 035.MI 035.MI.SA 039.S 041
Chapter 9: Estimating a Population Proportion
9.CE 2 001.CV 002.CV
9.R 8 070 071 073 074.S 076.S 077 079 082.S
9.1 9 002 004 005.MI 005.MI.SA 008 010 012 014 016
9.2 13 017.MI 017.MI.SA 019.S 020 022 024.MI.S 024.MI.SA 025.S 026 028 031.MI 031.MI.SA 033
9.3 23 034.MI 034.MI.SA 036 037.MI 037.MI.SA 038.MI.S 038.MI.SA.S 039 040.S 042.MI.S 042.MI.SA 044 046 047 048.S 049 050.S 051.S 053.S 055.S 057 058.S 060.S
9.4 6 062.S 064.MI.S 064.MI.SA 066.MI.S 066.MI.SA 067.S
Chapter 10: Asking and Answering Questions About a Population Proportion
10.CE 2 001.CV 002.CV
10.R 11 SYS.001.S 083 084 085 087 089 090.S 092 094.S 096.S 097
10.1 10 002 004 005 006 009.MI 009.MI.SA 010 014.MI 014.MI.SA 016
10.2 9 018 019 021.MI 021.MI.SA 023 025 026 030 031
10.3 5 032.S 033.MI.S 033.MI.SA 035.S 036
10.4 6 038 039 041.MI 041.MI.SA 042 044
10.5 21 ST.001.S 047 048 049 051.MI.S 051.MI.SA.S 052.MI.S 052.MI.SA.S 055.S 056.S 057 058 061 063.S 067 069.MI.S 069.MI.SA.S 071.S 073.MI.S 073.MI.SA.S 074.S
10.6 8 075 076 077 078 079 080 081 082
Chapter 11: Asking and Answering Questions About the Difference Between Two Population Proportions
11.AP 45 FR.001 FR.002 FR.003 FR.004 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041
11.CE 1 001.CV
11.R 4 033.S 035 038.S 039.S
11.1 10 ST.001.S 001.S 002.S 004.MI.S 004.MI.SA 005 006.MI.S 006.MI.SA 009.S 010.S
11.2 5 011 013.S 016 018.S 019.S
11.3 8 020.S 023.S 024.S 025.S 027.MI.S 027.MI.SA 031.S 032
Chapter 12: Asking and Answering Questions About a Population Mean
12.JMP 22 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022
12.R 7 SYS.001.S SYS.002.S 043 044 046.S 048.S 049.S
12.1 19 ST.001.S 002.MI.S 002.MI.SA 003 004.S 006.S 008.MI.S 008.MI.SA.S 009.S 010.S 012 013.MI.S 013.MI.SA.S 014.MI.S 014.MI.SA 015.S 018 020 021.S
12.2 15 ST.001.S 023.S 024.S 025.S 026.MI.S 026.MI.SA.S 027.S 029.S 031.MI 031.MI.SA 032.S 033.S 038.S 040.MI.S 040.MI.SA.S
Chapter 13: Asking and Answering Questions About the Difference Between Two Means
13.AP 40 FR.001 FR.002 FR.003 FR.004 FR.005 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035
13.CE 1 002.CV
13.JMP 20 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020
13.R 11 SYS.001.S SYS.002.S 081 082 084.S 085.S 086.S 088.S 089.S 092 094.S
13.1 2 001 002
13.2 21 005.MI.S 005.MI.SA.S 007.S 009 010.MI.S 010.MI.SA.S 013.MI.S 013.MI.SA 014.MI.S 014.MI.SA.S 016.S 017.MI.S 017.MI.SA.S 020.S 022.S 026 027.MI.S 027.MI.SA.S 029.S 030.MI.S 030.MI.SA.S
13.3 24 ST.001.S ST.002.S 032.S 033.S 035.S 036.MI.S 036.MI.SA.S 038.MI.S 038.MI.SA.S 040.S 043.S 044.S 046.MI.S 046.MI.SA.S 047.S 048.S 049.S 050.S 053.S 054.S 056.S 057.MI.S 057.MI.SA.S 058.S
13.4 20 059 060 062.MI.S 062.MI.SA.S 063.S 065.MI.S 065.MI.SA.S 066.S 068 070 071.S 072.MI.S 072.MI.SA.S 073 074 075 077.MI.S 077.MI.SA.S 078.S 079.S
Chapter 14: Learning from Categorical Data
14.AP 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
14.CE 1 001.CV
14.JMP 6 001 002 003 004 005 006
14.R 7 040.S 041.S 042.S 044.S 045.S 047.S 048
14.1 16 001.S 002.MI.S 002.MI.SA 003.MI.S 003.MI.SA.S 004.S 007.S 008.S 010.S 011.MI.S 011.MI.SA.S 012.S 014.S 015.MI.S 015.MI.SA.S 017.S
14.2 14 019.MI.S 019.MI.SA 020.S 021 023.S 026.S 032.S 033.MI.S 033.MI.SA 034.S 035.MI.S 035.MI.SA.S 036.S 038.S
Chapter 15: Understanding Relationships—Numerical Data
15.AP 17 FR.001 FR.002 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
15.R 4 046 047 048 050
15.1 11 001 002 003.MI.S 003.MI.SA.S 006.MI.S 006.MI.SA.S 007 009.S 010.S 011.MI 011.MI.SA
15.2 11 013 016 017 018.MI 018.MI.SA 020 021 022 026.S 027 029
15.3 11 030 031 033.MI 033.MI.SA 035 037 038 039 040.MI 040.MI.SA 043.S
Total 1521