Mind on Statistics 6th edition

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Jessica M. Utts and Robert F. Heckard
Publisher: Cengage Learning

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  • Chapter 1: Statistics Success Stories and Cautionary Tales
    • 1: Concept Explorations (2)
    • 1.1: What Is Statistics?
    • 1.2: Eight Statistical Stories with Morals
    • 1.3: The Common Elements in the Eight Stories
    • 1: Chapter Exercises (37)

  • Chapter 2: Turning Data into Information
    • 2: Concept Explorations (6)
    • 2.1: Raw Data (8)
    • 2.2: Types of Variables (13)
    • 2.3: Summarizing One or Two Categorical Variables (10)
    • 2.4: Exploring Features of Quantitative Data with Pictures (17)
    • 2.5: Numerical Summaries of Quantitative Variables (19)
    • 2.6: How to Handle Outliers (6)
    • 2.7: Bell-Shaped Distributions and Standard Deviations (18)
    • 2: Chapter Exercises (32)
    • 2: Labs (11)

  • Chapter 3: Relationships Between Quantitative Variables
    • 3: Concept Explorations (3)
    • 3.1: Looking for Patterns with Scatterplots (10)
    • 3.2: Describing Linear Patterns with a Regression Line (14)
    • 3.3: Measuring Strength and Direction with Correlation (19)
    • 3.4: Regression and Correlation Difficulties and Disasters (10)
    • 3.5: Correlation Does Not Prove Causation (11)
    • 3: Chapter Exercises (23)
    • 3: Labs (6)

  • Chapter 4: Relationships Between Categorical Variables
    • 4: Concept Explorations (1)
    • 4.1: Displaying Relationships Between Categorical Variables (12)
    • 4.2: Risk, Relative Risk, and Misleading Statistics about Risk (13)
    • 4.3: The Effect of a Third Variable and Simpson's Paradox (6)
    • 4.4: Assessing the Relationship in a 2 × 2 Table: Hypothesis Testing (18)
    • 4.5: Randomization Test for a 2 × 2 Table (7)
    • 4: Chapter Exercises (21)
    • 4: Labs (5)

  • Chapter 5: Sampling: Surveys and How to Ask Questions
    • 5: Concept Explorations (2)
    • 5.1: Collecting and Using Sample Data Wisely (18)
    • 5.2: Margin of Error, Confidence Intervals, and Sample Size (17)
    • 5.3: Choosing a Simple Random Sample (6)
    • 5.4: Additional Probability Sampling Methods (5)
    • 5.5: Difficulties and Disasters in Sampling (9)
    • 5.6: Pitfalls in Asking Survey Questions (12)
    • 5: Chapter Exercises (25)
    • 5: Labs (6)

  • Chapter 6: Gathering Useful Data for Examining Relationships
    • 6: Concept Explorations (1)
    • 6.1: Speaking the Language of Research Studies (12)
    • 6.2: Designing a Good Experiment (14)
    • 6.3: Designing a Good Observational Study (8)
    • 6.4: Difficulties and Disasters in Experiments and Observational Studies (14)
    • 6: Chapter Exercises (26)

  • Chapter 7: Probability
    • 7: Concept Explorations (2)
    • 7.1: Random Circumstances (6)
    • 7.2: Interpretations of Probability (10)
    • 7.3: Probability Definitions and Relationships (14)
    • 7.4: Basic Rules for Finding Probabilities (18)
    • 7.5: Conditional Probabilities and Bayes' Rule (18)
    • 7.6: Using Simulation to Estimate Probabilities (6)
    • 7.7: Flawed Intuitive Judgments about Probability (11)
    • 7: Chapter Exercises (22)
    • 7: Labs (5)

  • Chapter 8: Random Variables
    • 8: Concept Explorations (3)
    • 8.1: What Is a Random Variable? (6)
    • 8.2: Discrete Random Variables (15)
    • 8.3: Expectations for Random Variables (14)
    • 8.4: Binomial Random Variables (14)
    • 8.5: Continuous Random Variables (5)
    • 8.6: Normal Random Variables (20)
    • 8.7: Approximating Binomial Distribution Probabilities (6)
    • 8.8: Linear Combinations and Linear Transformations of Random Variables (10)
    • 8: Chapter Exercises (20)
    • 8: Labs (10)

  • Chapter 9: Understanding Sampling Distributions: Statistics as Random Variables
    • 9: Concept Explorations (2)
    • 9.1: Parameters, Statistics, and Statistical Inference (6)
    • 9.2: From Curiosity to Questions About Parameters (11)
    • 9.3: SD Module 0: An Overview of Sampling Distributions (8)
    • 9.4: SD Module 1: Sampling Distribution for One Sample Proportion (13)
    • 9.5: SD Module 2: Sampling Distribution for the Difference in Two Sample Proportions (8)
    • 9.6: SD Module 3: Sampling Distribution for One Sample Mean (8)
    • 9.7: SD Module 4: Sampling Distribution for the Sample Mean of Paired Differences (6)
    • 9.8: SD Module 5: Sampling Distribution for the Difference in Two Sample Means (5)
    • 9.9: Preparing for Statistical Inference: Standardized Statistics (25)
    • 9.10: Generalizations beyond the Big Five (8)
    • 9: Chapter Exercises (22)
    • 9: Labs (6)

  • Chapter 10: Estimating Proportions with Confidence
    • 10: Concept Explorations (4)
    • 10.1: CI Module 0: An Overview of Confidence Intervals (18)
    • 10.2: CI Module 1: Confidence Intervals for Population Proportions (22)
    • 10.3: CI Module 2: Confidence Intervals for the Difference in Two Population Proportions (9)
    • 10.4: Using Simulation to Calculate Confidence Intervals: Bootstrapping (8)
    • 10.5: Using Confidence Intervals to Guide Decisions (6)
    • 10: Chapter Exercises (27)
    • 10: Labs (6)

  • Chapter 11: Estimating Means with Confidence
    • 11: Concept Explorations (2)
    • 11.1: Introduction to Confidence Intervals for Means (20)
    • 11.2: CI Module 3: Confidence Intervals for One Population Mean (16)
    • 11.3: CI Module 4: Confidence Intervals for the Population Mean of Paired Differences (6)
    • 11.4: CI Module 5: Confidence Intervals for the Difference in Two Population Means (Independent Samples) (11)
    • 11.5: Using Simulation to Calculate Confidence Intervals: Bootstrapping for Means and Other Parameters (11)
    • 11.6: Understanding Any Confidence Interval (4)
    • 11: Chapter Exercises (20)
    • 11: Labs (6)

  • Chapter 12: Testing Hypotheses about Proportions
    • 12: Concept Explorations (5)
    • 12.1: HT Module 0: An Overview of Hypothesis Testing (38)
    • 12.2: HT Module 1: Testing Hypotheses about a Population Proportion (18)
    • 12.3: HT Module 2: Testing Hypotheses about the Difference in Two Population Proportions (12)
    • 12.4: Using Resampling to Estimate the p-Value for Testing Hypotheses About Two Proportions (8)
    • 12.5: Sample Size, p-Values, and Power (7)
    • 12.6: Understanding and Addressing Criticisms of Significance Testing (14)
    • 12: Chapter Exercises (26)
    • 12: Labs

  • Chapter 13: Testing Hypotheses about Means
    • 13: Concept Explorations (1)
    • 13.1: Introduction to Hypothesis Tests for Means (9)
    • 13.2: HT Module 3: Testing Hypotheses about One Population Mean (20)
    • 13.3: HT Module 4: Testing Hypotheses about the Population Mean of Paired Differences (10)
    • 13.4: HT Module 5: Testing Hypotheses about the Difference in Two Population Means (Independent Samples) (20)
    • 13.5: The Relationship Between Significance Tests and Confidence Intervals (6)
    • 13.6: Choosing an Appropriate Inference Procedure (6)
    • 13.7: Effect Size (9)
    • 13.8: Evaluating Significance in Research Reports (6)
    • 13: Chapter Exercises (17)
    • 13: Labs (6)

  • Chapter 14: Inference about Simple Regression
    • 14: Concept Explorations (1)
    • 14.1: Sample and Population Regression Models (11)
    • 14.2: Estimating the Standard Deviation for Regression (8)
    • 14.3: Inference about the Slope of a Linear Regression (8)
    • 14.4: Predicting y and Estimating Mean y at a Specific x (8)
    • 14.5: Checking Conditions for Using Regression Models for Inference (5)
    • 14: Chapter Exercises (16)
    • 14: Labs (6)

  • Chapter 15: More about Inference for Categorical Variables
    • 15: Concept Explorations (2)
    • 15.1: The Chi-Square Test for Two-Way Tables (16)
    • 15.2: Methods for Analyzing 2 × 2 Tables (10)
    • 15.3: Testing Hypotheses about One Categorical Variable: Goodness-of-Fit (10)
    • 15: Chapter Exercises (28)
    • 15: Labs (6)

  • Chapter 16: Analysis of Variance
    • 16: Concept Explorations (2)
    • 16.1: Comparing Means with an ANOVA F-Test (10)
    • 16.2: Details of One-Way Analysis of Variance (10)
    • 16.3: Other Methods for Comparing Populations (5)
    • 16.4: Two-Way Analysis of Variance (7)
    • 16: Chapter Exercises (18)
    • 16: Labs (5)

  • Chapter 17: Turning Information into Wisdom
    • 17: Concept Explorations (1)
    • 17.1: Beyond the Data
    • 17.2: Transforming Uncertainty Into Wisdom
    • 17.3: Making Personal Decisions
    • 17.4: Controlling Societal Risks
    • 17.5: Understanding Our World
    • 17.6: Getting to Know You
    • 17.7: Words to the Wise
    • 17: Chapter Exercises (34)

  • Chapter S1: Additional Discrete Random Variables
    • S1.1: Hypergeometric Distribution (12)
    • S1.2: Poisson Distribution (12)
    • S1.3: Multinomial Distribution (6)
    • S1.4: Negative Binomial and Geometric Distributions (10)

  • Chapter S2: Nonparametric Tests of Hypotheses
    • S2: Concept Explorations (1)
    • S2.1: The Sign Test (7)
    • S2.2: The Two-Sample Rank-Sum Test (10)
    • S2.3: The Wilcoxon Signed-Rank Test (7)
    • S2.4: The Kruskal-Wallis Test (5)

  • Chapter S3: Multiple Regression
    • S3: Concept Explorations (1)
    • S3.1: The Multiple Linear Regression Model
    • S3.2: Inference About Multiple Regression Models
    • S3.3: Checking Conditions for Multiple Linear Regression

  • Chapter S4: Two-Way Analysis of Variance
    • S4.1: Assumptions and Models for Two-Way ANOVA
    • S4.2: Testing for Main Effects and Interactions

  • Chapter S5: Ethics
    • S5.1: Ethical Treatment of Human and Animal Participants
    • S5.2: Assurance of Data Quality
    • S5.3: Appropriate Statistical Analyses
    • S5.4: Fair Reporting of Results

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


Engage your students' natural curiosity and motivate them with intriguing questions as you explain statistical topics in the context of interesting examples and case studies. Utts/Heckard's Mind on Statistics, 6th Edition, with WebAssign and a new SALT data analysis tool, emphasizes the conceptual development of statistical ideas and the importance of finding meaning in data. This edition balances statistical literacy with coverage of statistical methodology taught in introductory courses. Students develop statistical intuition by analyzing data and interpreting results, rather than relying on mathematical formulation. In addition, WebAssign with a new Statistical Analysis and Learning Tool (SALT) turns students into statistical thinkers.

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  • Read It links under each question quickly jump to the corresponding section of a complete, interactive eBook that lets students highlight and take notes as they read.
  • Watch It links provide step-by-step instruction with short, engaging videos that are ideal for visual learners.
  • SALT (Statistical Analysis and Learning Tool) is a data analysis tool for introductory level statistics courses that helps students gain improved conceptual understanding of statistics through visualization and analysis of datasets. SALT can be used on its own or as a tool to answer SALT-enabled questions in WebAssign.
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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 da...

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  • 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
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    • SPSS
    • R
  • A study guide helps students summarize the material and further practice the most important concepts.

Questions to Help Students Gain Interest and Assess Conceptual Understanding

  • Stats in Practice Video Questions (SIP) show students how Statistics applies in the real world. Short and current news videos introduce each module. Each video is accompanied by multiple-choice and discussion questions, so that students can understand real-world context of what they're learning and stay engaged throughout the whole module.
  • 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.

Tools to Explore Real Data with Technology

  • 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.
  • SALT Tutorial Questions (ST): Help your students understand how to use SALT in their WebAssign assignments. Students are provided with scaffolded instruction not only on the content, but how to use SALT to compute and analyze data.
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  • 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

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.

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Group Quantity Questions
Chapter PJT: Project
PJT.1 4 001 002 003 004
Chapter S1: Additional Discrete Random Variables
S1.1 12 001 002 003 005 006 007 009 010 011 013 014 015 501.LS
S1.2 12 017 019 020 022 023 024 025 026 027 028 030 032 501.LS 502.LS 503.LS 504.LS
S1.3 6 034 035 036 037 039 040 501.LS 502.LS
S1.4 10 041 042 043 044 045 046 047 048 049 051 501.LS 502.LS 503.LS 504.LS
Chapter S2: Nonparametric Tests of Hypotheses
S2.CE 1 001.CV
S2.1 7 001 002 005.S 006.S 007.S 008 009.S
S2.2 10 010 011 012 013 014.S 016.S 018.S 019.S 020 021
S2.3 7 022 023 025 026.S 027.S 028 029
S2.4 5 031 032.S 033 035.S 036.S
Chapter S3: Multiple Regression
S3.C 24 003 004 005 006 007 008 010 011 012 013 014 015 016 017 018 019 021 022 023 024 025 026 027 029
S3.CE 1 001.CV
Chapter S4: Two-Way Analysis of Variance
S4.C 24 003 004 005 006 007 008 009 010 011 012 015 016 017 018 019 021 022.S 023 024 025 026 027.S 028 029
Chapter S5: Ethics
S5.C 23 001 003 004 005 006 007 008 009 010 011 012 013 014 016 017 018 019 020 022 025 026 027 029
Chapter 1: Statistics Success Stories and Cautionary Tales
1.C 37 001 002 003 004 005 007 008 009 010 011 012 013 014 015 016 017 019 020 022.S 023.S 024.S 025 026 027 028 031 032 033 034 035 036 038 039 040 042 043 501.XP
1.CE 2 001.CV 001.SIP
1.2 501.LS
Chapter 2: Turning Data into Information
2.C 32 109 110 111 112 113 115 117 119.S 121 122 123 124 125.S 126 127 128 129 131.S 132 133 134 135 137.S 138 139.S 140 141 142.S 143.S 144.S 501.XP 502.XP.S
2.CE 6 001.CV 001.SIP 002.CV 003.CV 004.CV 005.CV
2.Lab 11 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS 002.TI
2.1 8 001 002 003 004 005 006 007 009 501.LS
2.2 13 011 012 013 014 015 016 017 018 019 020 021 025 026 501.LS 502.LS 503.LS 504.LS
2.3 10 027.S 028.S 029 030 031 032 033 035 037 038 501.LS 502.LS 503.LS
2.4 17 ST.001.S ST.002.S SYS.001.S 040 041 042 043 044.S 045 046 047 048 049 051 052 053 055 501.LS 502.LS.S 503.LS.S 504.LS 505.LS 506.LS 507.LS 508.LS 509.LS
2.5 19 058 059 061 062 063 064.S 065.S 066.S 067.S 068.S 069.S 072 073.S 074.S 075 076 077.S 078 079.S 501.LS 502.LS.S 503.LS.S 504.LS.S 505.LS.S 506.LS 507.LS 508.LS 509.LS 510.LS
2.6 6 SYS.001.S 080 081 082.S 083.S 085
2.7 18 086 087 088 089 090.S 092 093 094 095 096 097 098 101 102 104 105 106.S 107 501.LS
Chapter 3: Relationships Between Quantitative Variables
3.C 23 075 076 077 078 079 080 081 082 083 085.S 087 089 090.S 091.S 092.S 093.S 094.S 095.S 096.S 097.S 098.S 099.S 100.S
3.CE 3 001.CV 001.SIP 002.CV
3.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
3.1 10 001 002 003 004 007.S 008 009.S 010.S 011.S 012 501.LS
3.2 14 013 014 015 016 017 018 019 020 021 022 023 024 025 026 501.LS 502.LS.S 503.LS 504.LS
3.3 19 027 028 029 030 031 032 033 035 037 038 040 042 043 044 045 047 048.S 049 050.S 501.LS 502.LS 503.LS.S
3.4 10 051 052 053 054 055.S 057 058 060.S 061 062 501.LS.S
3.5 11 064 066 067 068 069 070 071 072 073 074 501.XP
Chapter 4: Relationships Between Categorical Variables
4.C 21 072 073 074 075 076.S 077.S 078.S 079.S 080 081 083 084 085 086 087 089 090 091 092 093 094
4.CE 1 001.SIP
4.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
4.1 12 001 002 003 004 005 006 007 008 009 010 011 014
4.2 13 015 016 017 018 019 020 021 022 023 024 025 026 027
4.3 6 034 035 036 037 038 039
4.4 18 040 041 042 043 044 045 046 047 048 052 053 054 055 056 058.S 059.S 060.S 061
4.5 7 063 065 067 068 069 070 071
Chapter 5: Sampling: Surveys and How to Ask Questions
5.C 25 083 086 087 088 089 090 091 092 093 094 095 096 097 098 099 101 102 103 106 107 108 109 110 111 502.XP
5.CE 2 001.CV 001.SIP
5.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
5.1 18 001 002 003 004 005 006 007 008 010 011 013 014 015 016 017 018 019 020 501.LS
5.2 17 023 024 025 026 027 028 029 031 032 035 036 037 038 039 040 041 501.XP
5.3 6 042 043 045 046 047 048 501.LS 502.LS 503.LS
5.4 5 050 051 052 053 055 501.LS 502.LS 503.LS 504.LS 505.LS 506.LS
5.5 9 057 058 059 060 062 063 065 066 067 501.LS 502.LS 503.LS 504.LS 505.LS
5.6 12 068 069 070 071 073 074 077 078 079 080 081 082 501.LS 502.LS
Chapter 6: Gathering Useful Data for Examining Relationships
6.C 26 061 062 063 064 065 066 068 069 070 071 072 073 074 075 076 077 079 081 083 085 086 087 089 090 091 093
6.CE 1 001.SIP
6.1 12 001 002 003 004 005 006 009 010 011 012 013 014 501.LS 502.LS 503.LS 504.LS 505.LS 506.LS 507.LS 508.LS 509.LS
6.2 14 017 018 019 021 022 023 024 026 027 028 029 030 031 032 501.LS 502.LS 503.LS 504.LS 505.LS 506.LS 507.LS 508.LS 509.LS 510.LS 511.LS.S
6.3 8 033 034 035 036 037 038 039 042
6.4 14 043 044 046 047 048 049 050 051 053 054 055 056 057 060
Chapter 7: Probability
7.C 22 105 106 109 111 112 113 114 115 116 117 118 120 122 123 124 125 126 127 128 129 501.XP 502.XP
7.CE 2 001.CV 001.SIP
7.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
7.1 6 001 002 003 005 006 007
7.2 10 008 009 010 011 012 014 015 017 018 019
7.3 14 020 021 023 024 025 026 027 028 029 030 032.S 033 035 037 501.LS 502.LS 503.LS 504.LS 505.LS
7.4 18 038 039 040 041 042 044 045 046 048 049 052 053 054 055 056 057 059 060 501.LS 502.LS 503.LS 504.LS 505.LS 506.LS 507.LS 508.LS
7.5 18 061 062 063 064 065 066 067 068 069 071 072 073 074 075 076 078 080 081 501.LS 502.LS
7.6 6 083 084 085 086 087 090
7.7 11 091 092 093 094 095 096 097 098 099 103 104
Chapter 8: Random Variables
8.C 20 102 104.S 105 106 107 108 109 111.S 113.S 114.S 115.S 116.S 117 118 120 121.S 122 501.XP.S 502.XP.S 503.XP 504.LS
8.CE 3 001.CV 001.SIP 002.CV
8.Lab 10 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS
8.1 6 001 002 003 004 006 008
8.2 15 009 010 011 012 013 014 015 017 018 020 021 022 023 501.XP 502.XP 503.LS 504.LS 505.LS.S 506.LS 507.LS 508.LS 509.LS 510.LS
8.3 14 026 027 028 030 031 032 033 034 035 036 037 038 040 501.XP 502.LS 503.LS
8.4 14 041 042 043 045.S 046 047 048.S 049 050.S 051.S 052.S 054.S 055 501.XP 502.LS 503.LS 504.LS 505.LS.S 506.LS 507.LS
8.5 5 057 058 059 060 062
8.6 20 ST.001.S ST.002.S SYS.001.S SYS.002.S 063.S 064.S 066.S 067.S 069.S 070.S 071.S 072.S 073.S 074.S 075.S 077.S 078.S 079.S 501.XP.S 502.XP.S 503.LS 504.LS.S 505.LS.S 506.LS 507.LS 508.LS.S 509.LS.S 510.LS.S 511.LS.S 512.LS.S 513.LS.S 514.LS.S 515.LS.S 516.LS.S 517.LS.S 518.LS.S 519.LS.S 520.LS.S 521.LS.S 522.LS.S
8.7 6 081.S 082.S 083.S 084.S 085.S 087.S 501.LS.S 502.LS.S
8.8 10 089.S 090.S 091 092 093 095 097.S 098.S 099.S 100.S
Chapter 9: Understanding Sampling Distributions: Statistics as Random Variables
9.C 22 127 129 130 131 132.S 134 137 138.S 139 140.S 141 142.S 143 144 145.S 146.S 147 149.S 150.S 152 153 154 501.LS 502.LS
9.CE 2 001.CV 001.SIP
9.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
9.1 6 001 002 003 005 006 007
9.2 11 009 010 011 012 014 015 016 017 018 021 022
9.3 8 023 024 025 026 027 028 029 031
9.4 13 033 034 035 036 037 038 039 040 041 042.S 043 045 046 501.LS 502.LS 503.LS 504.LS 505.LS 506.LS 507.LS.S
9.5 8 050 051 052 053 054.S 056 057 058 501.LS
9.6 8 059 060 061 062 063 064 066 067 501.LS 502.LS 503.LS.S
9.7 6 069 070 071 072 074 075 501.LS
9.8 5 076 077 078 079.S 081 501.LS
9.9 25 082 083 084 085.S 086.S 088.S 089.S 091.S 092 093.S 094 096.S 097 098 099.S 100 101 102 103 105 106.S 107 108.S 109.S 112.S
9.10 8 113 114 115 117 118 121 124 126
Chapter 10: Estimating Proportions with Confidence
10.C 27 079 081.S 082.S 083.S 085 087 088.S 089.S 090.S 091.S 092 094.S 095.S 096 097.S 098.S 099 100 101.S 102.S 103.S 104 105.S 501.XP.S 502.XP.S 503.XP.S 504.XP
10.CE 4 001.CV 001.SIP 002.CV 002.SIP
10.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
10.1 18 001 004 005 006 007 009 011 012 013 014 015 016 017 018 019.S 020.S 021 022.S
10.2 22 023.S 024.S 025.S 026.S 027.S 028.S 029.S 030.S 032.S 033.S 034.S 035.S 036.S 038.S 039.S 041 043 044.S 045.S 046 047.S 049.S 501.LS.S
10.3 9 050 051 053 054.S 055.S 056.S 057 058.S 059.S 501.LS.S 502.LS.S
10.4 8 061 062 063 064 066.S 067 068 070
10.5 6 071 072.S 073 074 075.S 078
Chapter 11: Estimating Means with Confidence
11.C 20 082 084.S 085 086.S 087.S 088.S 089.S 090.S 091 093 094.S 095 096 097 098.S 099.S 100.S 101.S 102.S 501.XP
11.CE 2 001.CV 001.SIP
11.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
11.1 20 ST.001.S 001 002 003 004 005 006 007.S 008.S 009 011 012 013 016 017 018 019 020 021 023
11.2 16 SYS.001.S 025.S 026.S 027.S 028.S 029.S 030.S 032.S 033.S 035 036.S 037 039 040 041 042 502.LS.S 503.LS.S 504.LS.S
11.3 6 044.S 045.S 046.S 047 048.S 050.S 501.LS.S 502.LS.S 503.LS.S 504.LS.S 505.LS.S 506.LS.S
11.4 11 ST.001.S SYS.001.S 052.S 053.S 054.S 055 056 057 058.S 060.S 061.S 501.LS 502.LS.S
11.5 11 062 063 064 065 066 067 069 070.S 071 072 073
11.6 4 076 077 078 079
Chapter 12: Testing Hypotheses about Proportions
12.C 26 119 120 121.S 122 125.S 126 127 128 129 130 131.S 132 133.S 134.S 135.S 138 139.S 140.S 141.S 142.S 144 145 146.S 147.S 148.S 501.XP.S
12.CE 5 001.CV 001.SIP 002.CV 003.CV 004.CV
12.1 38 001 002 003 004 005 006 007 008 009 010 011 012 014 015 017 018 019 020 023 024 025 026 028 029 030 031 032 037 038 039 040 041 042 044 045 046 047 048 501.LS 502.LS.S 503.LS.S 504.LS 505.LS 506.LS 507.LS
12.2 18 ST.001.S SYS.001.S 049.S 050 052 053 054 055 056.S 058.S 059.S 060 061 062.S 063.S 066.S 067.S 501.XP.S 502.LS.S
12.3 12 068.S 069.S 070.S 071.S 072 073.S 075.S 076.S 077.S 079.S 081 501.XP.S 502.LS 503.LS 504.LS 505.LS 506.LS.S 507.LS.S
12.4 8 082 083 084 085 086 087 088 091
12.5 7 092 093.S 094 095 096 098.S 099
12.6 14 101 104 105 106 107 110 111 112 113 114 115 116 117 118
Chapter 13: Testing Hypotheses about Means
13.C 17 102 103 104 105.S 107.S 108.S 110.S 111.S 112.S 113.S 114.S 116.S 117 118.S 119.S 120.S 121.S
13.CE 1 001.SIP
13.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
13.1 9 001 002 003 004 005 006 007 009 010
13.2 20 ST.001.S SYS.001.S 013 014 015 016 017 018.S 020 022 023.S 024.S 025.S 026.S 027.S 028.S 030.S 031.S 032 501.XP.S 502.LS 503.LS.S 504.LS 505.LS 506.LS 507.LS.S 508.LS.S 509.LS.S 510.LS.S 511.LS.S 512.LS 513.LS 514.LS 515.LS.S 516.LS 517.LS 518.LS 519.LS 520.LS
13.3 10 033 034 035.S 036.S 037 039.S 042.S 043.S 044.S 045.S 501.LS
13.4 20 ST.001.S SYS.001.S 047.S 048.S 049 050 051 052 053 054 055 057.S 058.S 059.S 060.S 061.S 063.S 064.S 065 066 501.LS 502.LS 504.LS
13.5 6 069 070 071 072 073 075
13.6 6 076 077 078 079 081 082
13.7 9 083 084 086 087 088 089 091 092 093
13.8 6 094 095 097 099 100 101
Chapter 14: Inference about Simple Regression
14.C 16 051 052 053 054 055 056.S 057 058.S 059 062 063.S 064 065.S 066.S 067.S 501.XP
14.CE 1 001.SIP
14.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
14.1 11 001 002 003 005 006 007 009 010 011 012 013
14.2 8 015 016 017 018 019 021 023 024
14.3 8 025 026 027 029 030 031 032 033 501.LS.S 502.LS.S 503.LS 504.LS 505.LS.S 506.LS.S 507.LS.S 508.LS.S 509.LS.S
14.4 8 035 036 037 038 039 040 041 044 501.LS.S 502.LS.S 503.LS.S
14.5 5 045 046 047 048 050 501.LS.S
Chapter 15: More about Inference for Categorical Variables
15.C 28 045.S 046.S 048.S 049.S 050 051.S 052.S 053.S 055.S 056.S 057 059 060 061.S 062 063.S 064.S 065.S 066.S 067.S 070 071.S 072.S 073 074.S 075.S 501.XP.S 502.XP
15.CE 2 001.CV 001.SIP
15.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
15.1 16 001 003 004 005.S 006.S 007.S 008.S 009.S 010 011.S 012.S 014 015.S 016.S 017.S 018.S 501.LS 502.LS 503.LS 504.LS.S 505.LS.S
15.2 10 021 022 023.S 024 026.S 027 028 030 031.S 032.S 501.LS 502.LS
15.3 10 033 034 035 036 037.S 038.S 040.S 042.S 043.S 044.S 501.LS 502.LS.S
Chapter 16: Analysis of Variance
16.C 18 041 042 043 044 045 046.S 047 048 049 052 053.S 054.S 055.S 056.S 057.S 058 059 501.XP
16.CE 2 001.CV 001.SIP
16.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
16.1 10 001 002 003 004 005 006.S 008 009 010 012 501.LS
16.2 10 014 015 016 018 019 021.S 022 023 024 025 501.LS 502.LS 503.LS
16.3 5 026 027 028 030 031
16.4 7 032 034 035 036 037 038 039 501.LS 502.LS
Chapter 17: Turning Information into Wisdom
17.C 34 001 002 003 004 005 006 007 009 010 014 015 017 018 019 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 038 040 041 042
17.CE 1 001.SIP
Total 1703 (234)