# Mind on Statistics 5th edition

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

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## Textbook Resources

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• College Success Toolkit
• Math Mindset
• Utts and Heckard Mind on Statistics 5e: Stats in Practice Video Questions
• Utts and Heckard Mind on Statistics 5e: Labs - TI Calculators
• Utts and Heckard Mind on Statistics 5e: Labs - Excel
• Utts and Heckard Mind on Statistics 5e: Labs - JMP
• Utts and Heckard Mind on Statistics 5e: Labs - Minitab
• Utts and Heckard Mind on Statistics 5e: Labs - SPSS
• Utts and Heckard Mind on Statistics 5e: Labs - R
• Utts and Heckard Mind on Statistics 5e: Project Milestones

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

• 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 (18)
• 1: Extra Problems (1)
• 1: Active Examples
• 1: Concept Questions (4)
• 1: Test Bank (8)

• Chapter 2: Turning Data into Information
• 2: Concept Explorations (6)
• 2: SALT Tutorial - Supporting Sections 2.3, 2.4, 2.5, and 2.6 (2)
• 2.1: Raw Data (6)
• 2.2: Types of Variables (8)
• 2.3: Summarizing One or Two Categorical Variables (8)
• 2.4: Exploring Features of Quantitative Data with Pictures (7)
• 2.5: Numerical Summaries of Quantitative Variables (9)
• 2.6: How to Handle Outliers (2)
• 2.7: Bell-Shaped Distributions and Standard Deviations (12)
• 2: Chapter Exercises (11)
• 2: Dataset Exercises (3)
• 2: Extra Problems (2)
• 2: Select Your Scenario (beta) - Supporting Sections 2.3, 2.4, 2.5, and 2.6 (2)
• 2: Active Examples (3)
• 2: JMP Simulations (23)
• 2: Concept Questions (49)
• 2: Labs (11)
• 2: Test Bank (413)

• Chapter 3: Relationships Between Quantitative Variables
• 3: Concept Explorations (3)
• 3: SALT Tutorial
• 3.1: Looking for Patterns with Scatterplots (5)
• 3.2: Describing Linear Patterns with a Regression Line (14)
• 3.3: Measuring Strength and Direction with Correlation (16)
• 3.4: Regression and Correlation Difficulties and Disasters (5)
• 3.5: Correlation Does Not Prove Causation (5)
• 3: Chapter Exercises (6)
• 3: Dataset Exercises (4)
• 3: Extra Problems
• 3: Select Your Scenario (beta)
• 3: Active Examples (3)
• 3: JMP Simulations (14)
• 3: Concept Questions (14)
• 3: Labs (6)
• 3: Test Bank (109)

• Chapter 4: Relationships Between Categorical Variables
• 4: Concept Explorations (1)
• 4.1: Displaying Relationships Between Categorical Variables (6)
• 4.3: The Effect of a Third Variable and Simpson's Paradox (3)
• 4.4: Assessing the Statistical Significance of a 2 × 2 Table (9)
• 4: Chapter Exercises (7)
• 4: Dataset Exercises (2)
• 4: Extra Problems
• 4: Active Examples (2)
• 4: JMP Simulations (2)
• 4: Concept Questions (8)
• 4: Labs (5)
• 4: Test Bank (41)

• Chapter 5: Sampling: Surveys and How to Ask Questions
• 5: Concept Explorations (2)
• 5.1: Collecting and Using Sample Data Wisely (9)
• 5.2: Margin of Error, Confidence Intervals, and Sample Size (13)
• 5.3: Choosing a Simple Random Sample (3)
• 5.4: Additional Probability Sampling Methods (3)
• 5.5: Difficulties and Disasters in Sampling (4)
• 5.6: Pitfalls in Asking Survey Questions (6)
• 5: Chapter Exercises (12)
• 5: Extra Problems
• 5: Active Examples (7)
• 5: Concept Questions (18)
• 5: Labs (6)
• 5: Test Bank (107)

• Chapter 6: Gathering Useful Data for Examining Relationships
• 6: Concept Explorations (1)
• 6.1: Speaking the Language of Research Studies (6)
• 6.2: Designing a Good Experiment (7)
• 6.3: Designing a Good Observational Study (4)
• 6.4: Difficulties and Disasters in Experiments and Observational Studies (7)
• 6: Chapter Exercises (13)
• 6: Extra Problems
• 6: Active Examples (2)
• 6: Concept Questions (16)
• 6: Test Bank (18)

• Chapter 7: Probability
• 7: Concept Explorations (2)
• 7.1: Random Circumstances (3)
• 7.2: Interpretations of Probability (6)
• 7.3: Probability Definitions and Relationships (7)
• 7.4: Basic Rules for Finding Probabilities (11)
• 7.5: Conditional Probabilities and Bayes' Rule (11)
• 7.6: Using Simulation to Estimate Probabilities (3)
• 7.7: Flawed Intuitive Judgments about Probability (6)
• 7: Chapter Exercises (17)
• 7: Extra Problems (1)
• 7: Active Examples (5)
• 7: Concept Questions (20)
• 7: Labs (5)
• 7: Test Bank (9)

• Chapter 8: Random Variables
• 8: Concept Explorations (3)
• 8: SALT Tutorial - Supporting Sections 8.4 and 8.6 (2)
• 8.1: What Is a Random Variable? (4)
• 8.2: Discrete Random Variables (10)
• 8.3: Expectations for Random Variables (11)
• 8.4: Binomial Random Variables (10)
• 8.5: Continuous Random Variables (2)
• 8.6: Normal Random Variables (15)
• 8.7: Approximating Binomial Distribution Probabilities (3)
• 8.8: Sums, Differences, and Combinations of Random Variables (8)
• 8: Chapter Exercises (9)
• 8: Extra Problems (2)
• 8: Select Your Scenario (beta) - Supporting Sections 8.4 and 8.6 (2)
• 8: Active Examples (8)
• 8: JMP Simulations (5)
• 8: Concept Questions (30)
• 8: Labs (10)
• 8: Test Bank (142)

• Chapter 9: Understanding as Sampling Distributions: Statistics as Random Variables
• 9: Concept Explorations (2)
• 9.1: Parameters, Statistics, and Statistical Inference (3)
• 9.2: From Curiosity to Questions About Parameters (6)
• 9.3: SD Module 0: An Overview of Sampling Distributions (4)
• 9.4: SD Module 1: Sampling Distribution for One Sample Proportion (9)
• 9.5: SD Module 2: Sampling Distribution for the Difference in Two Sample Proportions (7)
• 9.6: SD Module 3: Sampling Distribution for One Sample Mean (5)
• 9.7: SD Module 4: Sampling Distribution for the Sample Mean of Paired Differences (3)
• 9.8: SD Module 5: Sampling Distribution for the Difference in Two Sample Means (2)
• 9.9: Preparing for Statistical Inference: Standardized Statistics (12)
• 9.10: Generalizations beyond the Big Five (6)
• 9: Chapter Exercises (8)
• 9: Dataset Exercises (2)
• 9: Extra Problems
• 9: Active Examples (4)
• 9: Concept Questions (24)
• 9: Labs (6)
• 9: Test Bank (112)

• Chapter 10: Estimating Proportions with Confidence
• 10: Concept Explorations (4)
• 10: SALT Tutorial - Supporting Sections 10.1, 10.2, and 10.3
• 10.1: CI Module 0: An Overview of Confidence Intervals (9)
• 10.2: CI Module 1: Confidence Intervals for Population Proportions (11)
• 10.3: CI Module 2: Confidence Intervals for the Difference in Two Population Proportions (4)
• 10.4: Using Confidence Intervals to Guide Decisions (3)
• 10: Chapter Exercises (8)
• 10: Dataset Exercises (4)
• 10: Extra Problems (4)
• 10: Select Your Scenario (beta) - Supporting Sections 10.1, 10.2, and 10.3
• 10: Active Examples (2)
• 10: JMP Simulations (6)
• 10: Concept Questions (12)
• 10: Labs (6)
• 10: Test Bank (33)

• Chapter 11: Estimating Means with Confidence
• 11: Concept Explorations (2)
• 11: SALT Tutorial - Supporting Sections 11.1, 11.2, and 11.4 (2)
• 11.1: Introduction to Confidence Intervals for Means (10)
• 11.2: CI Module 3: Confidence Intervals for One Population Mean (9)
• 11.3: CI Module 4: Confidence Intervals for the Population Mean of Paired Differences (3)
• 11.4: CI Module 5: Confidence Intervals for the Difference in Two Population Means (Independent Samples) (7)
• 11.5: Understanding Any Confidence Interval (2)
• 11: Chapter Exercises (10)
• 11: Dataset Exercises (5)
• 11: Extra Problems (1)
• 11: Select Your Scenario (beta) - Supporting Sections 11.1, 11.2, and 11.4 (2)
• 11: Active Examples (2)
• 11: JMP Simulations (15)
• 11: Concept Questions (10)
• 11: Labs (6)
• 11: Test Bank (120)

• Chapter 12: Testing Hypotheses about Proportions
• 12: Concept Explorations (5)
• 12: SALT Tutorial - Supporting Sections 12.2 and 12.3 (1)
• 12.1: HT Module 0: An Overview of Hypothesis Testing (19)
• 12.2: HT Module 1: Testing Hypotheses about a Population Proportion (8)
• 12.3: HT Module 2: Testing Hypotheses about the Difference in Two Population Proportions (8)
• 12.4: Sample Size, Statistical Significance, and Practical Importance (5)
• 12: Chapter Exercises (12)
• 12: Dataset Exercises (2)
• 12: Extra Problems
• 12: Select Your Scenario (beta) - Supporting Sections 12.2 and 12.3 (1)
• 12: Active Examples (3)
• 12: JMP Simulations (8)
• 12: Concept Questions (14)
• 12: Labs
• 12: Test Bank (70)

• Chapter 13: Testing Hypotheses about Means
• 13: Concept Explorations (1)
• 13: SALT Tutorial - Supporting Sections 13.2, 13.3, and 13.4 (2)
• 13.1: Introduction to Hypothesis Tests for Means (4)
• 13.2: HT Module 3: Testing Hypotheses about One Population Mean (9)
• 13.3: HT Module 4: Testing Hypotheses about the Population Mean of Paired Differences (7)
• 13.4: HT Module 5: Testing Hypotheses about the Difference in Two Population Means (Independent Samples) (8)
• 13.5: The Relationship Between Significance Tests and Confidence Intervals (3)
• 13.6: Choosing an Appropriate Inference Procedure (3)
• 13.7: Effect Size (4)
• 13.8: Evaluating Significance in Research Reports (3)
• 13: Chapter Exercises (6)
• 13: Dataset Exercises (3)
• 13: Extra Problems
• 13: Select Your Scenario (beta) - Supporting Sections 13.2, 13.3, and 13.4 (2)
• 13: Active Examples (2)
• 13: JMP Simulations (11)
• 13: Concept Questions (12)
• 13: Labs (6)
• 13: Test Bank (231)

• Chapter 14: Inference about Simple Regression
• 14: Concept Explorations (1)
• 14: SALT Tutorial
• 14.1: Sample and Population Regression Models (4)
• 14.2: Estimating the Standard Deviation for Regression (4)
• 14.3: Inference about the Slope of a Linear Regression (4)
• 14.4: Predicting y and Estimating Mean y at a Specific x (4)
• 14.5: Checking Conditions for Using Regression Models for Inference (2)
• 14: Chapter Exercises (8)
• 14: Dataset Exercises (2)
• 14: Extra Problems (1)
• 14: Select Your Scenario (beta)
• 14: Active Examples (3)
• 14: JMP Simulations (7)
• 14: Concept Questions (16)
• 14: Labs (6)
• 14: Test Bank (110)

• Chapter 15: More about Inference for Categorical Variables
• 15: Concept Explorations (2)
• 15.1: The Chi-Square Test for Two-Way Tables (8)
• 15.2: Methods for Analyzing 2 × 2 Tables (5)
• 15.3: Testing Hypotheses about One Categorical Variable: Goodness-of-Fit (5)
• 15: Chapter Exercises (8)
• 15: Dataset Exercises (2)
• 15: Extra Problems (2)
• 15: Active Examples (3)
• 15: JMP Simulations (2)
• 15: Concept Questions
• 15: Labs (6)
• 15: Test Bank (41)

• Chapter 16: Analysis of Variance
• 16: Concept Explorations (2)
• 16.1: Comparing Means with an ANOVA F-Test (7)
• 16.2: Details of One-Way Analysis of Variance (9)
• 16.3: Other Methods for Comparing Populations (2)
• 16.4: Two-Way Analysis of Variance (4)
• 16: Chapter Exercises (4)
• 16: Dataset Exercises (4)
• 16: Extra Problems (1)
• 16: Active Examples (5)
• 16: JMP Simulations (6)
• 16: Concept Questions (18)
• 16: Labs (5)
• 16: Test Bank (246)

• 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: Control of Societal Risks
• 17.5: Understanding Our World
• 17.6: Getting to Know You
• 17.7: Words to the Wise
• 17: Chapter Exercises (17)
• 17: Extra Problems
• 17: Active Examples (1)
• 17: Concept Questions (2)

• Chapter S1: Additional Discrete Random Variables
• S1.1: Hypergeometric Distribution (7)
• S1.2: Poisson Distribution (7)
• S1.3: Multinomial Distribution

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

• Chapter S3: Multiple Regression
• S3: Concept Explorations (1)
• S3.1: The Multiple Linear Regression Model
• S3.2: Inference for 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)

Mind on Statistics, Fifth Edition, by Utts and Heckard, helps students develop a conceptual understanding of statistical ideas by showing them how to find meaning in data. This textbook engages students' curiosity with intriguing questions, and explains statistical topics in the context of interesting, useful examples, and case studies. The WebAssign component for this text engages students with an interactive eBook, Active Examples with worked-out solutions, and lecture video textbook resources.

#### New for Spring '21

• Additional SALT Tutorial Questions added to 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.
• Additional Select Your Scenario Questions were added. Select Your Scenario 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.
• New Concept Videos were added. Concept Videos are 7-10 minutes in length and are designed to help students with big picture understanding of statistics.
• New Concept Video Questions were added providing students with a concept video along with two to three comprehension questions.
• Questions updated with SALT (Statistical Analysis and Learning Tool), including questions with frequency data and questions requiring the implementation of a Chi-Square test.

#### New for Fall '20 / Spring '21 Academic Year

• 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.
• #### 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...

### Instructor Product Features

• Course Packs with ready-to-use assignments were built by subject matter experts specifically for this textbook. They are designed to save you time and can be easily customized to meet your teaching goals. Course Packs are available for Stats in Practice Video Questions, Labs, and Project Milestones.
• Test Banks: A pool of over 1,000 assessments for use in quizzes, tests, and exams.
• 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. Lecture PowerPoint slides are also available.
• Use the Textbook Edition Upgrade Tool to automatically update all of your assignments from the previous edition to corresponding questions in this textbook.

### Student Learning Tools

• 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.
• Active Examples (AE) guide students through the process needed to master a concept and include worked-out solutions.
• 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

### 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 Questions (CQ) provide a new way of engaging with non-computational questions. Students enter a free response before they choose a multiple-choice answer, closing the gap between homework and test preparedness.
• 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.
• Simulation Questions by JMP (JMP): Have your students understand concepts by utilizing real data. Students must discover the answer to guided questions by interacting with a simulation of real data in our JMP interactive applet within WebAssign.
• 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

## 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
AE - Active Example
SIP - Stats in Practice Video Question
JMP - Simulation Question by JMP
CQ - Concept Question
Lab - Lab
PJT - Project Milestone
TB - Test Bank
XP - Extra Problem
S - SALT
ST - SALT Tutorial

##### 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 S1: Additional Discrete Random Variables
S1.E 14 005 006 007 009 010 011 013 015 018 019 022 023 024 028
Chapter S2: Nonparametric Tests of Hypotheses
S2.CE 1 001.CV
Chapter S3: Multiple Regression
S3.CE 1 001.CV
Chapter 1: Statistics Success Stories and Cautionary Tales
1.CE 2 001.CV 001.SIP
1.CQ 4 001 002 003 004
1.E 19 001 002 003 005 007 008 010 012 013 016 022.S 025 028 032 033 035 036 042 501.XP
1.TB 8 001 002 003 004 005 006 007 008
Chapter 2: Turning Data into Information
2.AE 3 004 005 016.S
2.CE 6 001.CV 001.SIP 002.CV 003.CV 004.CV 005.CV
2.CQ 49 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049
2.E 68 001 002 003 005 006 007 011 012 013 014 015 017 018 019 027 029 030 031 032 033 035 037 040 042 043 044 045 048 052 058 059 061 062 063 065.S 066.S 067 074.S 081 085 086 087 090.S 092 094 096 097 098 101 102 105 106.S 111 113 115 117 119.S 124 125.S 126 131.S 133 134 137.S 139.S 142.S 501.XP 502.XP.S
2.JMP 23 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023
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.ST 2 001.S 002.S
2.SYS 2 001.S 002.S
2.TB 413 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413
Chapter 3: Relationships Between Quantitative Variables
3.AE 3 001 013 020
3.CE 3 001.CV 001.SIP 002.CV
3.CQ 14 001 002 003 004 005 006 007 008 009 010 011 012 013 014
3.E 55 002 003 004 007.S 008 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 037 038 042 043 045 047 048.S 049 050.S 051 055.S 058 060.S 062 064 068 070 072 073 075 078 079 080 081 085.S 091.S 094.S 097.S 098.S
3.JMP 14 001 002 003 004 005 006 007 008 009 010 011 012 013 014
3.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
3.TB 109 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109
Chapter 4: Relationships Between Categorical Variables
4.AE 2 007 016
4.CE 1 001.SIP
4.CQ 8 001 002 003 004 005 006 007 008
4.E 35 003 006 008 010 011 014 015 019 022 023 024 025 026 027 034 036 037 040 041 044 045 047 052 055 058.S 059.S 063 064 066.S 069.S 070 071 073 081 083
4.JMP 2 001 002
4.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
4.TB 41 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041
Chapter 5: Sampling: Surveys and How to Ask Questions
5.AE 7 002 006 011 013 015 016 019
5.CE 2 001.CV 001.SIP
5.CQ 18 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018
5.E 50 005 006 010 013 014 015 016 018 019 023 024 025 026 027 028 032 035 037 038 039 040 041 045 046 048 050 051 052 060 063 065 067 071 073 074 077 079 081 083 088 089 091 093 094 096 099 102 106 108 110
5.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
5.TB 107 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107
Chapter 6: Gathering Useful Data for Examining Relationships
6.AE 2 001 009
6.CE 1 001.SIP
6.CQ 16 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016
6.E 37 001 002 006 009 011 013 019 023 024 027 029 030 031 035 036 038 039 044 046 047 048 049 056 057 061 064 065 068 069 070 073 077 079 081 087 089 093
6.TB 18 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018
Chapter 7: Probability
7.AE 5 002 010 012 023 026
7.CE 2 001.CV 001.SIP
7.CQ 20 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020
7.E 65 001 003 005 008 009 010 012 014 019 020 021 025 028 030 032 033 038 039 040 042 048 053 054 055 056 057 060 061 062 063 064 065 067 068 069 070 071 072 075 077 078 084 086 088 089 091 095 101 103 104 105 106 107 108 110 112 114 115 116 117 118 119 120 121 501.XP
7.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
7.TB 9 001 002 003 004 005 006 007 008 009
Chapter 8: Random Variables
8.AE 8 003 012 019 021 023 024 026 027
8.CE 3 001.CV 001.SIP 002.CV
8.CQ 30 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030
8.E 74 001 002 003 004 009 010 013 014 015 017 018 020 021 022 027 030 031 032 033 034 035 036 037 038 040 042 043 044 045.S 046 047 048.S 050.S 052.S 055 057 058 063.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 080.S 081.S 082.S 085.S 089.S 090.S 091 092 093 095.S 096.S 097.S 100.S 101 102 103 104 107.S 109.S 115.S 116 501.XP.S 502.XP.S
8.JMP 5 001 002 003 004 005
8.Lab 10 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 002.Excel 002.JMP 002.Minitab 002.R 002.SPSS
8.ST 2 001.S 002.S
8.SYS 2 001.S 002.S
8.TB 142 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142
Chapter 9: Understanding as Sampling Distributions: Statistics as Random Variables
9.AE 4 001 002 011 012
9.CE 2 001.CV 001.SIP
9.CQ 24 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024
9.E 67 001 006 007 009 010 012 014 016 018 026 027 028 031 034 036 037 039 040 042.S 043 045 046 050 051 052 054.S 056 057 058 059 060 061 062 064 070 072 074 078 079.S 084 086.S 088.S 092.S 094 096.S 098 099.S 101 103 106.S 107 113 114 115 118 121 124 129 134 137 138.S 139 143 145.S 147 150 152
9.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
9.TB 112 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112
Chapter 10: Estimating Proportions with Confidence
10.AE 2 005 011
10.CE 4 001.CV 001.SIP 002.CV 501.XP.SIP
10.CQ 12 001 002 003 004 005 006 007 008 009 010 011 012
10.E 43 005 006 009 011 012 013 014 017 021 023.S 025.S 026.S 027.S 028.S 032.S 034.S 041 044.S 046 047.S 054.S 056.S 058.S 059.S 062.S 063 064 071.S 072.S 073.S 077 081.S 084.S 085.S 086 089.S 091.S 092 093 501.XP.S 502.XP.S 503.XP.S 504.XP
10.JMP 6 001 002 003 004 005 006
10.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
10.TB 33 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033
Chapter 11: Estimating Means with Confidence
11.AE 2 008 009
11.CE 2 001.CV 001.SIP
11.CQ 10 001 002 003 004 005 006 007 008 009 010
11.E 47 003 004 005 007.S 012 016 017 018 020 023 026.S 029.S 030.S 032.S 035 036 037 041 042 044.S 046.S 047 054.S 055 056 057 058.S 060 061.S 064 065 073 074.S 075.S 076.S 077.S 078.S 081 082.S 083 085.S 086.S 087.S 088 089.S 090.S 501.XP
11.JMP 15 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015
11.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
11.ST 2 001.S 002.S
11.SYS 2 001.S 002.S
11.TB 120 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120
Chapter 12: Testing Hypotheses about Proportions
12.AE 3 004 007 018
12.CE 5 001.CV 001.SIP 002.CV 003.CV 004.CV
12.CQ 14 001 002 003 004 005 006 007 008 009 010 011 012 013 014
12.E 54 005 006 007 008 010 011 019 020 021 022 024 025 026 027 028 029 031 036 037 041.S 042.S 044 045 046 050.S 051.S 052 060.S 061.S 062.S 064.S 065.S 068.S 071.S 073 074.S 076 078 083 085 089 090 091.S 092 095.S 096 097 099 100 109 112.S 113.S 116.S 118.S
12.JMP 8 001 002 003 004 005 006 007 008
12.ST 1 001.S
12.SYS 1 001.S
12.TB 70 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070
Chapter 13: Testing Hypotheses about Means
13.AE 2 008 016
13.CE 1 001.SIP
13.CQ 12 001 002 003 004 005 006 007 008 009 010 011 012
13.E 50 002 004 006 007 016 020.S 022 023 024 025.S 026.S 030.S 031.S 033 034 035.S 036.S 037 042.S 043.S 048.S 050 051 054 055.S 056.S 058.S 059.S 065 066 067 070 073 075 077 080 081 087 088 094 095 096 097 098 101.S 104.S 105.S 112.S 113 115.S
13.JMP 11 001 002 003 004 005 006 007 008 009 010 011
13.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
13.ST 2 001.S 002.S
13.SYS 2 001.S 002.S
13.TB 231 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234
Chapter 14: Inference about Simple Regression
14.AE 3 005 010 011
14.CE 1 001.SIP
14.CQ 16 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016
14.E 29 001 003 005 007 011 012 015 017 021 022 025 029 031 035 036 040 044 046 048 049 050 051 052 053 054 055 059 061 501.XP
14.JMP 7 001 002 003 004 005 006 007
14.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
14.TB 110 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110
Chapter 15: More about Inference for Categorical Variables
15.AE 3 001 010 013
15.CE 2 001.CV 001.SIP
15.E 30 004 005.S 006.S 007.S 008.S 009.S 012.S 016.S 021 022 024 026.S 028 033 035 037 042.S 043.S 045.S 046.S 051.S 053.S 057 059 061 062 066 068 501.XP.S 502.XP
15.JMP 2 001 002
15.Lab 6 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS 001.TI
15.TB 41 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041
Chapter 16: Analysis of Variance
16.AE 5 001 003 006 011 015
16.CE 2 001.CV 001.SIP
16.CQ 18 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018
16.E 31 001 002 003 004 005 006.S 009 014 015 016 018 019 021 022 023 025 027 030 032 035 037 038 042 043 045 049 052 053 057 059 501.XP
16.JMP 6 001 002 003 004 005 006
16.Lab 5 001.Excel 001.JMP 001.Minitab 001.R 001.SPSS
16.TB 246 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069 070 071 072 073 074 075 076 077 078 079 080 081 082 083 084 085 086 087 088 089 090 091 092 093 094 095 096 097 098 099 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246
Chapter 17: Turning Information into Wisdom
17.AE 1 002
17.CE 1 001.SIP
17.CQ 2 001 002
17.E 17 001 003 004 010 019 025 028 029 030 031 032 033 034 035 036 040 041
Total 3164