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Mind on Statistics, Australian Version 1st edition

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Helen MacGillivray, Jessica M. Utts, and Robert F. Heckard
Publisher: Brooks/Cole

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Table of Contents

  • Chapter 1: Thinking Statistically
    • 1.1: What is statistics?
    • 1.2: Some statistical stories in real and complex problems
    • 1.3: Some examples of what can go wrong at the beginning of data investigations
    • 1.4: The discovery of knowledge
    • 1: Chapter Exercises
    • 1: Active Examples

  • Chapter 2: Gathering and Preparing Useful Data
    • 2.1: Datasets and types of investigations
    • 2.2: Some practicalities and challenges in planning data investigations
    • 2.3: Types of data and variables
    • 2.4: Surveys
    • 2.5: Designing Experiments
    • 2.6: Some types of observational studies
    • 2.7: Some cautions in experiments and observational studies
    • 2: Chapter Exercises (69)
    • 2: Active Examples (1)

  • Chapter 3: Turning Data into Graphical Information
    • 3.1: Categorical data
    • 3.2: Graphs and plots for one continuous variable
    • 3.3: Continuous and categorical data
    • 3.4: More than one continuous variable
    • 3.5: Outliers
    • 3.6: Good graphs and bad graphs
    • 3: Chapter Exercises (21)
    • 3: Active Examples

  • Chapter 4: Data Features and Summary Statistics
    • 4.1: Commenting on features of data
    • 4.2: Measures of location
    • 4.3: Measures of spread
    • 4.4: Shape
    • 4.5: Parameters, models and estimates
    • 4: Chapter Exercises (24)
    • 4: Active Examples

  • Chapter 5: Investigating Categorical Variables and Their Relationships
    • 5.1: Summarising and presenting categorical data
    • 5.2: More than two categorical variables
    • 5.3: One categorical variable: testing a set of proportions
    • 5.4: p-values and testing statistical hypotheses
    • 5.5: Testing independence of two categorical variables
    • 5.6: Risk, relative risk and misleading statistics about risk
    • 5: Chapter Exercises (59)
    • 5: Active Examples

  • Chapter 6: Probability Essentials for Data Analysis
    • 6.1: What is probability?
    • 6.2: Where do values of probabilities come from?
    • 6.3: What is a random variable?
    • 6.4: Expected values and standard deviations of random variables
    • 6.5: Three special distributions
    • 6.6: Normal probability plots
    • 6: Chapter Exercises (64)
    • 6: Active Examples (4)

  • Chapter 7: Estimating Proportions with Confidence
    • 7.1: Percentages and proportions abound
    • 7.2: Confidence intervals for proportions
    • 7.3: Background for confidence intervals for proportions
    • 7.4: Confidence intervals for the difference in two proportions
    • 7.5: Confidence intervals and decisions
    • 7.6: Sample size to estimate a proportion
    • 7: Chapter Exercises (39)
    • 7: Active Examples (1)

  • Chapter 8: Analysis of Variance: Investigating Effects of Categorical Variables on a Continuous Variable
    • 8.1: Some examples of data investigations that include continuous responses and possible categorical explanatory variables
    • 8.2: One-way ANOVA
    • 8.3: Assumptions and diagnostics for ANOVA
    • 8.4: Other methods for investigating effects of a categorical variable on a continuous variable
    • 8.5: Multiple comparisons
    • 8.6: Two-way ANOVA
    • 8.7: More on continuous response and categorical explanatory variables
    • 8.8: Models, notation and calculations for ANOVA
    • 8: Chapter Exercises (40)
    • 8: Active Examples

  • Chapter 9: Regression: Investigating Relationships Between Continuous Variables
    • 9.1: Some examples of data investigations that include continuous responses and quantitative explanatory variables
    • 9.2: Simple linear regression
    • 9.3: Messages from residuals
    • 9.4: Multiple regression
    • 9.5: Some formulae in regression
    • 9: Chapter Exercises (28)
    • 9: Active Examples

  • Chapter 10: Interval Estimation: One or Two Continuous Variables
    • 10.1: The sample mean
    • 10.2: Confidence interval for the mean of a continuous variable
    • 10.3: Difference between two means
    • 10.4: Confidence interval for difference between two means
    • 10.5: Tolerance intervals for individual values
    • 10.6: Confidence interval for a standard deviation
    • 10.7: Sample size required to estimate a mean with a desired precision
    • 10: Chapter Exercises (41)
    • 10: Active Examples (2)

  • Chapter 11: Testing Hypotheses about Means, Proportions and Variances in One and Two Samples
    • 11.1: Overview of statistical hypothesis testing
    • 11.2: Testing hypotheses about a proportion
    • 11.3: Testing hypotheses about the difference in two proportions
    • 11.4: Connection with testing independence in contingency tables
    • 11.5: Testing hypotheses about one mean
    • 11.6: Testing hypotheses about the mean of paired differences
    • 11.7: Testing hypotheses about the difference between two means
    • 11.8: Non-parametric tests and medians
    • 11.9: Tests for one or two standard deviations
    • 11.10: The relationship between tests and confidence intervals
    • 11.11: t-tests and ANOVA: correspondences and pitfalls of t-testing in real investigations
    • 11.12: The rejection region approach to hypothesis testing
    • 11.13: Sample size, statistical significance, practical importance and effect size
    • 11: Chapter Exercises (70)
    • 11: Active Examples (3)

  • Chapter 12: More on Probability, Random Variables and Distributions
    • 12.1: Events
    • 12.2: Probability Rules
    • 12.3: Independence and conditional probability
    • 12.4: Using conditional probabilities
    • 12.5: Bayes' theorem
    • 12.6: Continuous distributions
    • 12.7: A very special process: the Poisson
    • 12: Chapter Exercises (44)
    • 12: Active Examples

  • Chapter 13: Sums and Differences of Random Variables
    • 13.1: Examples for which this chapter is needed
    • 13.2: Sums and differences of two random variables
    • 13.3: Means and variances of linear combinations of random variables
    • 13.4: Linear combinations of normal random variables
    • 13.5: Sums of some other independent random variables
    • 13.6: The sample mean and the central limit theorem
    • 13.7: Combining "errors
    • 13: Chapter Exercises (21)
    • 13: Active Examples

  • Chapter 14: Some Further Data Situations
    • 14.1: Binary logistic regression
    • 14.2: Failure and survival data
    • 14: Chapter Exercises
    • 14: Active Examples

Questions Available within WebAssign

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AE
 Active Example


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Group Quantity Questions
Chapter 1: Thinking Statistically
1 0  
Chapter 2: Gathering and Preparing Useful Data
AE 1 010
E 69 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064 065 066 067 068 069
Chapter 3: Turning Data into Graphical Information
E 21 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021
Chapter 4: Data Features and Summary Statistics
E 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
Chapter 5: Investigating Categorical Variables and Their Relationships
E 59 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059
Chapter 6: Probability Essentials for Data Analysis
AE 4 011 016 018 022
E 64 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044 045 046 047 048 049 050 051 052 053 054 055 056 057 058 059 060 061 062 063 064
Chapter 7: Estimating Proportions with Confidence
AE 1 012
E 39 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039
Chapter 8: Analysis of Variance: Investigating Effects of Categorical Variables on a Continuous Variable
E 40 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040
Chapter 9: Regression: Investigating Relationships Between Continuous Variables
E 28 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028
Chapter 10: Interval Estimation: One or Two Continuous Variables
AE 2 011 012
E 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 11: Testing Hypotheses about Means, Proportions and Variances in One and Two Samples
AE 3 001 009 024
E 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 12: More on Probability, Random Variables and Distributions
E 44 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043 044
Chapter 13: Sums and Differences of Random Variables
E 21 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021
Total 531  
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