The Basic Practice of Statistics 7th edition

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David S. Moore, William I. Notz, and Michael A. Fligner
Publisher: W. H. Freeman

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  • Chapter 1: Picturing Distributions with Graphs
    • 1.1: Individuals and variables (1)
    • 1.2: Categorical variables: pie charts and bar graphs (3)
    • 1.3: Quantitative variables: histograms (1)
    • 1.4: Interpreting histograms
    • 1.5: Quantitative variables: stemplots (2)
    • 1.6: Time plots (1)
    • 1: Check Your Skills (10)
    • 1: Exercises (19)
    • 1: Exploring the Web
    • 1: Extra Problems (4)

  • Chapter 2: Describing Distributions with Numbers
    • 2.1: Measuring center: the mean (2)
    • 2.2: Measuring center: the median
    • 2.3: Comparing the mean and the median (3)
    • 2.4: Measuring variability: the quartiles
    • 2.5: The five-number summary and boxplots (2)
    • 2.6: Spotting suspected outliers and modified boxplots (2)
    • 2.7: Measuring variability: the standard deviation
    • 2.8: Choosing measures of center and variability (3)
    • 2.9: Using technology
    • 2.10: Organizing a statistical problem (2)
    • 2: Check Your Skills (10)
    • 2: Exercises (18)
    • 2: Exploring the Web
    • 2: Extra Problems (12)

  • Chapter 3: The Normal Distributions
    • 3.1: Density curves (2)
    • 3.2: Describing density curves (2)
    • 3.3: Normal distributions
    • 3.4: The 68–95–99.7 rule (2)
    • 3.5: The standard Normal distribution (2)
    • 3.6: Finding Normal proportions
    • 3.7: Using the standard Normal table (3)
    • 3.8: Finding a value given a proportion (2)
    • 3: Check Your Skills (10)
    • 3: Exercises (27)
    • 3: Exploring the Web
    • 3: Extra Problems (19)

  • Chapter 4: Scatterplots and Correlation
    • 4.1: Explanatory and response variables (3)
    • 4.2: Displaying relationships: scatterplots (1)
    • 4.3: Interpreting scatterplots (1)
    • 4.4: Adding categorical variables to scatterplots
    • 4.5: Measuring linear association: correlation (1)
    • 4.6: Facts about correlation (2)
    • 4: Check Your Skills (10)
    • 4: Exercises (18)
    • 4: Exploring the Web
    • 4: Extra Problems (4)

  • Chapter 5: Regression
    • 5.1: Regression lines (3)
    • 5.2: The least-squares regression line
    • 5.3: Using technology (2)
    • 5.4: Facts about least-squares regression (1)
    • 5.5: Residuals (3)
    • 5.6: Influential observations (3)
    • 5.7: Cautions about correlation and regression (3)
    • 5.8: Association does not imply causation (3)
    • 5: Check Your Skills (10)
    • 5: Exercises (26)
    • 5: Exploring the Web
    • 5: Extra Problems

  • Chapter 6: Two-Way Tables
    • 6.1: Marginal distributions (2)
    • 6.2: Conditional distributions (3)
    • 6.3: Simpson's paradox (2)
    • 6: Check Your Skills (7)
    • 6: Exercises (14)
    • 6: Exploring the Web
    • 6: Extra Problems

  • Chapter 7: Exploring Data: Part I Review
    • 7: Test Yourself (33)
    • 7: Supplementary Exercises (15)
    • 7: Extra Problems (1)

  • Chapter 8: Producing Data: Sampling
    • 8.1: Population versus sample (3)
    • 8.2: How to sample badly (2)
    • 8.3: Simple random samples (3)
    • 8.4: Inference about the population (1)
    • 8.5: Other sampling designs (2)
    • 8.6: Cautions about sample surveys (1)
    • 8.7: The impact of technology (1)
    • 8: Check Your Skills (7)
    • 8: Exercises (16)
    • 8: Exploring the Web
    • 8: Extra Problems (5)

  • Chapter 9: Producing Data: Experiments
    • 9.1: Observation versus experiment (3)
    • 9.2: Subjects, factors, and treatments (3)
    • 9.3: How to experiment badly (1)
    • 9.4: Randomized comparative experiments (2)
    • 9.5: The logic of randomized comparative experiments (2)
    • 9.6: Cautions about experimentation (2)
    • 9.7: Matched pairs and other block designs (3)
    • 9: Check Your Skills (9)
    • 9: Exercises (19)
    • 9: Exploring the Web
    • 9: Extra Problems (1)

  • Chapter 10: Data Ethics
    • 10.1: Institutional review boards (1)
    • 10.2: Informed consent (1)
    • 10.3: Confidentiality (1)
    • 10.4: Clinical trials
    • 10.5: Behavioral and social science experiments (1)
    • 10: Check Your Skills
    • 10: Exercises (6)
    • 10: Exploring the Web
    • 10: Extra Problems

  • Chapter 11: Producing Data: Part II Review
    • 11: Test Yourself (14)
    • 11: Supplementary Exercises (6)
    • 11: Extra Problems (1)

  • Chapter 12: Introducing Probability
    • 12.1: The idea of probability
    • 12.2: The search for randomness (3)
    • 12.3: Probability models (3)
    • 12.4: Probability rules (4)
    • 12.5: Finite and discrete probability models (3)
    • 12.6: Continuous probability models (3)
    • 12.7: Random variables (2)
    • 12.8: Personal probability (2)
    • 12: Check Your Skills (10)
    • 12: Exercises (25)
    • 12: Exploring the Web
    • 12: Extra Problems (28)

  • Chapter 13: General Rules of Probability
    • 13.1: Independence and the multiplication rule (3)
    • 13.2: The general addition rule (2)
    • 13.3: Conditional probability (3)
    • 13.4: The general multiplication rule (3)
    • 13.5: Independence again (1)
    • 13.6: Tree diagrams (4)
    • 13.7: Bayes' rule
    • 13: Check Your Skills (10)
    • 13: Exercises (30)
    • 13: Exploring the Web
    • 13: Extra Problems (15)

  • Chapter 14: Binomial Distributions
    • 14.1: The binomial setting and binomial distributions
    • 14.2: Binomial distributions in statistical sampling (4)
    • 14.3: Binomial probabilities
    • 14.4: Using technology (3)
    • 14.5: Binomial mean and standard deviation (2)
    • 14.6: The Normal approximation to binomial distributions (3)
    • 14: Check Your Skills (9)
    • 14: Exercises (22)
    • 14: Exploring the Web
    • 14: Extra Problems (8)

  • Chapter 15: Sampling Distributions
    • 15.1: Parameters and statistics (2)
    • 15.2: Statistical estimation and the law of large numbers
    • 15.3: Sampling distributions (2)
    • 15.4: The sampling distribution of (3)
    • 15.5: The central limit theorem (2)
    • 15.6: Sampling distributions and statistical significance
    • 15: Check Your Skills (7)
    • 15: Exercises (19)
    • 15: Exploring the Web
    • 15: Extra Problems (16)

  • Chapter 16: Confidence Intervals: The Basics
    • 16.1: The reasoning of statistical estimation (2)
    • 16.2: Margin of error and confidence level (1)
    • 16.3: Confidence intervals for a population mean (3)
    • 16.4: How confidence intervals behave (3)
    • 16: Check Your Skills (8)
    • 16: Exercises (7)
    • 16: Exploring the Web
    • 16: Extra Problems (9)

  • Chapter 17: Tests of Significance: The Basics
    • 17.1: The reasoning of tests of significance (1)
    • 17.2: Stating hypotheses (5)
    • 17.3: P-value and statistical significance (3)
    • 17.4: Tests for a population mean (2)
    • 17.5: Significance from a table (3)
    • 17.6: Resampling: significance from a simulation
    • 17: Check Your Skills (9)
    • 17: Exercises (13)
    • 17: Exploring the Web
    • 17: Extra Problems (8)

  • Chapter 18: Inference in Practice
    • 18.1: Conditions for inference in practice (3)
    • 18.2: Cautions about confidence intervals (4)
    • 18.3: Cautions about significance tests (4)
    • 18.4: Planning studies: sample size for confidence intervals (2)
    • 18.5: Planning studies: the power of a statistical test (4)
    • 18: Check Your Skills (9)
    • 18: Exercises (25)
    • 18: Exploring the Web
    • 18: Extra Problems (11)

  • Chapter 19: From Data Production to Inference: Part III Review
    • 19: Test Yourself (38)
    • 19: Supplementary Exercises (16)
    • 19: Extra Problems

  • Chapter 20: Inference about a Population Mean
    • 20.1: Conditions for inference about a mean (2)
    • 20.2: The t distributions (2)
    • 20.3: The one-sample t confidence interval (2)
    • 20.4: The one-sample t test (2)
    • 20.5: Using technology
    • 20.6: Matched pairs t procedures (1)
    • 20.7: Robustness of t procedures (2)
    • 20.8: Resampling and standard errors
    • 20: Check Your Skills (9)
    • 20: Exercises (18)
    • 20: Exploring the Web
    • 20: Extra Problems (12)

  • Chapter 21: Comparing Two Means
    • 21.1: Two-sample problems (1)
    • 21.2: Comparing two population means
    • 21.3: Two-sample t procedures (1)
    • 21.4: Using technology (1)
    • 21.5: Robustness again (4)
    • 21.6: Details of the t approximation (1)
    • 21.7: Avoid the pooled two-sample t procedures
    • 21.8: Avoid inference about standard deviations
    • 21.9: Permutation tests
    • 21: Check Your Skills (9)
    • 21: Exercises (23)
    • 21: Exploring the Web
    • 21: Extra Problems (8)

  • Chapter 22: Inference about a Population Proportion
    • 22.1: The sample proportion (2)
    • 22.2: Large-sample confidence intervals for a proportion (2)
    • 22.3: Choosing the sample size (2)
    • 22.4: Significance tests for a proportion (3)
    • 22.5: Plus four confidence intervals for a proportion (3)
    • 22: Check Your Skills (7)
    • 22: Exercises (6)
    • 22: Exploring the Web
    • 22: Extra Problems (18)

  • Chapter 23: Comparing Two Proportions
    • 23.1: Two-sample problems: proportions
    • 23.2: The sampling distribution of a difference between proportions
    • 23.3: Large-sample confidence intervals for comparing proportions
    • 23.4: Using technology
    • 23.5: Significance tests for comparing proportions (3)
    • 23.6: Plus four confidence intervals for comparing proportions (1)
    • 23: Check Your Skills (6)
    • 23: Exercises (16)
    • 23: Exploring the Web
    • 23: Extra Problems (7)

  • Chapter 24: Inference about Variables: Part IV Review
    • 24: Test Yourself (24)
    • 24: Supplementary Exercises (15)
    • 24: Extra Problems (14)

  • Chapter 25: Two Categorical Variables: The Chi-Square Test
    • 25.1: Two-way tables (1)
    • 25.2: The problem of multiple comparisons (1)
    • 25.3: Expected counts in two-way tables (1)
    • 25.4: The chi-square test statistic
    • 25.5: Cell counts required for the chi-square test
    • 25.6: Using technology (2)
    • 25.7: Uses of the chi-square test: independence and homogeneity (1)
    • 25.8: The chi-square distributions (1)
    • 25.9: The chi-square test for goodness of fit (5)
    • 25: Check Your Skills (10)
    • 25: Exercises (11)
    • 25: Exploring the Web
    • 25: Extra Problems (11)

  • Chapter 26: Inference for Regression
    • 26.1: Conditions for regression inference
    • 26.2: Estimating the parameters (1)
    • 26.3: Using technology (2)
    • 26.4: Testing the hypothesis of no linear relationship (3)
    • 26.5: Testing lack of correlation (2)
    • 26.6: Confidence intervals for the regression slope (3)
    • 26.7: Inference about prediction (2)
    • 26.8: Checking the conditions for inference (2)
    • 26: Check Your Skills (9)
    • 26: Exercises (23)
    • 26: Exploring the Web
    • 26: Extra Problems (13)

  • Chapter 27: One-Way Analysis of Variance: Comparing Several Means
    • 27.1: Comparing several means
    • 27.2: The analysis of variance F test (1)
    • 27.3: Using technology (1)
    • 27.4: The idea of analysis of variance
    • 27.5: Conditions for ANOVA (2)
    • 27.6: F distributions and degrees of freedom (2)
    • 27.7: Some details of ANOVA (3)
    • 27: Check Your Skills (2)
    • 27: Exercises (11)
    • 27: Exploring the Web
    • 27: Extra Problems (20)

  • Chapter 28: Nonparametric Tests
    • 28.1: Comparing two samples: the Wilcoxon rank sum test
    • 28.2: The Normal approximation for W
    • 28.3: Using technology
    • 28.4: What hypotheses does Wilcoxon test?
    • 28.5: Dealing with ties in rank tests (2)
    • 28.6: Matched pairs: the Wilcoxon signed rank test
    • 28.7: The Normal approximation for W+ (3)
    • 28.8: Dealing with ties in the signed rank test
    • 28.9: Comparing several samples: the Kruskal–Wallis test
    • 28.10: Hypotheses and conditions for the Kruskal–Wallis test
    • 28.11: The Kruskal–Wallis test statistic
    • 28: Check Your Skills (8)
    • 28: Exercises
    • 28: Exploring the Web
    • 28: Extra Problems

  • Chapter 29: Multiple Regression
    • 29.1: Parallel regression lines (2)
    • 29.2: Estimating parameters
    • 29.3: Using technology
    • 29.4: Inference for multiple regression
    • 29.5: Interaction (4)
    • 29.6: The general multiple linear regression model (1)
    • 29.7: The woes of regression coefficients
    • 29.8: A case study for multiple regression
    • 29.9: Inference for regression parameters (1)
    • 29.10: Checking the conditions for inference (2)
    • 29: Check Your Skills (10)
    • 29: Exercises
    • 29: Exploring the Web
    • 29: Extra Problems

  • Chapter 30: More about Analysis of Variance
    • 30.1: Beyond one-way ANOVA
    • 30.2: Follow-up analysis: Tukey pairwise multiple comparisons
    • 30.3: Follow-up analysis: contrasts
    • 30.4: Two-way ANOVA: conditions, main effects, and interaction
    • 30.5: Inference for two-way ANOVA
    • 30.6: Some details of two-way ANOVA
    • 30: Check Your Skills
    • 30: Exercises
    • 30: Exploring the Web
    • 30: Extra Problems

  • Chapter 31: Statistical Process Control
    • 31.1: Processes
    • 31.2: Describing processes (2)
    • 31.3: The idea of statistical process control (1)
    • 31.4: charts for process monitoring (1)
    • 31.5: s charts for process monitoring
    • 31.6: Using control charts (1)
    • 31.7: Setting up control charts
    • 31.8: Comments on statistical control (2)
    • 31.9: Don't confuse control with capability
    • 31.10: Control charts for sample proportions
    • 31.11: Control limits for p charts (4)
    • 31: Check Your Skills (4)
    • 31: Exercises (3)
    • 31: Exploring the Web
    • 31: Extra Problems


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Group Quantity Questions
Chapter 1: Picturing Distributions with Graphs
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Chapter 2: Describing Distributions with Numbers
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Chapter 3: The Normal Distributions
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Chapter 4: Scatterplots and Correlation
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Chapter 5: Regression
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Chapter 6: Two-Way Tables
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Chapter 7: Exploring Data: Part I Review
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Chapter 8: Producing Data: Sampling
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Chapter 9: Producing Data: Experiments
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Chapter 10: Data Ethics
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Chapter 11: Producing Data: Part II Review
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Chapter 12: Introducing Probability
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Chapter 13: General Rules of Probability
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Chapter 14: Binomial Distributions
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Chapter 15: Sampling Distributions
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Chapter 16: Confidence Intervals: The Basics
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Chapter 17: Tests of Significance: The Basics
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Chapter 18: Inference in Practice
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Chapter 19: From Data Production to Inference: Part III Review
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Chapter 20: Inference about a Population Mean
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Chapter 21: Comparing Two Means
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Chapter 22: Inference about a Population Proportion
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Chapter 23: Comparing Two Proportions
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Chapter 24: Inference about Variables: Part IV Review
24.E 53 001 002 003 004 005 009 019 020 021 022 023 025 026 027 028 029 031 032 040 041 042 043 044 045 046 048 049 050 051 052 053 054 055 056 057 060 061 062 063 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP 507.XP 508.XP 509.XP 510.XP 511.XP 512.XP 513.XP 514.XP
Chapter 25: Two Categorical Variables: The Chi-Square Test
25.E 44 002 004 006 008 009 010 013 014 015 016 017 018 019 020 021 023 024 025 026 027 028 029 033 035 036 037 039 041 044 045 048 049 050 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP 507.XP 508.XP 509.XP 510.XP 511.XP
Chapter 26: Inference for Regression
26.E 60 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 039 040 042 043 044 045 046 047 048 049 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP 507.XP 508.XP 509.XP 510.XP 511.XP 512.XP 513.XP
Chapter 27: One-Way Analysis of Variance: Comparing Several Means
27.E 42 001 003 008 009 010 011 012 013 014 015 023 024 025 026 027 028 029 031 032 040 041 043 501.XP 502.XP 503.XP 504.XP 505.XP 506.XP 507.XP 508.XP 509.XP 510.XP 511.XP 512.XP 513.XP 514.XP 515.XP 516.XP 517.XP 518.XP 519.XP 520.XP
Chapter 28: Nonparametric Tests
28.E 13 016 017 020 021 022 033 035 036 037 038 039 040 041
Chapter 29: Multiple Regression
29.E 20 001 002 011 012 013 016 018 027 029 030 031 032 033 034 035 036 037 038 039 040
Chapter 30: More about Analysis of Variance
30 0  
Chapter 31: Statistical Process Control
31.E 18 004 005 007 009 019 025 026 027 029 030 031 032 034 035 041 042 043 044
Total 1325