Solutions manual for Introduction to Statistical Investigations 2nd edition by Nathan Tintle, Beth L. Chance, George W. Cobb, et al.
SOLUTIONS MANUAL

Solutions manual for Introduction to Statistical Investigations 2nd edition by Nathan Tintle, Beth L. Chance, George W. Cobb, et al.

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Pages
155
File size
7.15 MB
Format
Digital PDF
About this ebook
Solutions manual for Introduction to Statistical Investigations by Nathan Tintle, Beth L. Chance, George W. Cobb, et al. is an innovative introductory statistics textbook. It is highly regarded for prioritizing an immersive, simulation-based inference approach (using applets, coin flips, and tactile shuffling) over formula-heavy traditional methods to build conceptual understanding. [1, 2, 3, 4, 5]
The book is structured around a core six-step statistical investigation framework: asking a research question, designing a study, exploring the data, drawing inferences, formulating conclusions, and looking back/ahead. [1]
Core Chapter Breakdown & Topics Covered
The textbook is organized into three main parts, covering foundational inference, comparative studies, and advanced modeling: [1]
Part 1: Four Pillars of Inference
  • Chapter 1 – Significance: Covers p-values, chance models, simulation-based tests, and z-scores for a single proportion.
  • Chapter 2 – Generalization: Examines sampling, bias, and inference for a single mean.
  • Chapter 3 – Estimation: Focuses on confidence intervals and the 2SD rule.
  • Chapter 4 – Causation: Explores experimental design, confounding, and random assignment. [1, 2, 3, 4, 5]
Part 2: Comparing Groups
  • Chapter 5 – Two Proportions: Simulation and theory-based tests (z-test) for comparing proportions.
  • Chapter 6 – Two Means: Covers t-tests and simulation-based methods for comparing averages.
  • Chapter 7 – Paired Data: Analyzes matched pairs and repeated measures using simulation and t-tests. [1, 2, 3, 4]
Part 3: Advanced Variations & Multivariable Modeling
  • Chapter 8 – Multiple Proportions: Covers Chi-square tests and simulation for multi-group data.
  • Chapter 9 – Multiple Means: Covers ANOVA and F-tests for comparing several groups.
  • Chapter 10 – Two Quantitative Variables: Introduces scatterplots, correlation, and linear regression.
  • Chapter 11 – Modeling Randomness: Covers probability fundamentals, random variables, and distributions. [1, 2, 3, 4]

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Solution-manual-for-Introduction-to-Statistical-Investigations-2e-Tintle.pdf 7.15 MB

Topics

Advanced Variations & Multivariable Modeling and inference for a single mean. and z-scores for a single proportion ANOVA and F-tests for comparing several groups Causation: Explores experimental design chance models Chi-square tests and simulation for multi-group data. Paired Data: Analyzes matched pairs and repeated measures probability fundamentals random variables and distributions sampling bias scatterplots correlation and linear regression Significance: Covers p-values simulation-based tests Two Means: Covers t-tests and simulation-based methods Two Proportions: Simulation and theory-based tests (z-test)
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