Mind on Statistics, Australian & New Zealand Version 2nd edition

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Helen MacGillivray, Jessica M. Utts, and Robert F. Heckerd
Publisher: Cengage Learning

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  • Chapter 1: Thinking Statistically
    • 1.1: What is statistics?
    • 1.2: Some statistical stories in real and complex problems
    • 1.3: Statistics starts before data are collected
    • 1.4: The discovery of knowledge
    • 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 (9)
    • 2.3: Types of data and variables (15)
    • 2.4: Surveys (23)
    • 2.5: Designing experiments
    • 2.6: Some types of observational studies (18)
    • 2.7: Some cautions in experiments and observational studies (4)
    • 2: Active Examples (1)

  • Chapter 3: Turning Data into Graphical Information
    • 3.1: Exploratory data analysis (EDA)
    • 3.2: Categorical data (5)
    • 3.3: Graphs and plots for one continuous variable
    • 3.4: Continuous and categorical data (6)
    • 3.5: More than one continuous variable (9)
    • 3.6: Outlying observations (1)
    • 3.7: Good graphs and bad graphs
    • 3: Active Examples

  • Chapter 4: Data Summaries and Inferential Concepts
    • 4.1: Features of quantitative data
    • 4.2: Measures of location
    • 4.3: Measures of spread or dispersion
    • 4.4: Shape (15)
    • 4.5: Estimates and interval estimation: confidence intervals
    • 4.6: Answering questions
    • 4.7: Bell-shaped distributions (9)
    • 4: Active Examples

  • Chapter 5: Investigating Categorical Variables and Their Relationships
    • 5.1: Background for categorical data
    • 5.2: More than two categorical variables (8)
    • 5.3: One categorical variable: testing a set of proportions
    • 5.4: p-values and testing statistical hypotheses (12)
    • 5.5: Testing independence of two categorical variables (17)
    • 5.6: Risk, relative risk and misleading statistics about risk (22)
    • 5: Active Examples

  • Chapter 6: Probability Essentials for Data Analysis
    • 6.1: What is probability?
    • 6.2: Where do values of probabilities come from? (9)
    • 6.3: What is a random variable? (9)
    • 6.4: Expected values, standard deviations, medians, quartiles and percentiles of random variables (9)
    • 6.5: Parameters and estimates
    • 6.6: Three special distributions (37)
    • 6.7: Normal probability plots
    • 6: Active Examples (4)

  • Chapter 7: Estimating Proportions with Confidence
    • 7.1: Percentages and proportions abound
    • 7.2: Confidence intervals for proportions (25)
    • 7.3: Confidence intervals for the difference in two proportions (6)
    • 7.4: Sample size to estimate a proportion (4)
    • 7.5: Background for confidence intervals for proportions
    • 7.6: Confidence intervals and decisions
    • 7: Active Examples (1)

  • Chapter 8: Analysis of Variance: Categorical Predictors, Continuous Response
    • 8.1: 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 (6)
    • 8.4: Multiple comparisons
    • 8.5: Two-way ANOVA (21)
    • 8.6: More on continuous response and categorical explanatory variables (1)
    • 8.7: Other methods for investigating effects of a categorical variable on a continuous variable (5)
    • 8.8: Models, notation and calculations for ANOVA (7)
    • 8: Active Examples

  • Chapter 9: Regression: Investigating Relationships Between Quantitative Variables
    • 9.1: Some examples of data investigations that include continuous responses and quantitative explanatory variables
    • 9.2: Simple linear regression (14)
    • 9.3: Messages from residuals
    • 9.4: Multiple regression (14)
    • 9.5: Some formulae in regression
    • 9: Active Examples

  • Chapter 10: Interval Estimation and Quantitative Variables
    • 10.1: Sample statistics as estimates
    • 10.2: Confidence interval for the mean of a quantitative variable (10)
    • 10.3: Interval estimates for the median (2)
    • 10.4: Confidence interval for difference between two means (18)
    • 10.5: Tolerance intervals for individual values (6)
    • 10.6: Confidence interval for a standard deviation
    • 10.7: Sample size required to estimate a mean with a desired precision (5)
    • 10: Active Examples (2)

  • Chapter 11: Testing Hypotheses in One and Two Samples
    • 11.1: Overview of statistical hypothesis testing (4)
    • 11.2: Testing hypotheses about a proportion (15)
    • 11.3: Testing hypotheses about the difference in two proportions (9)
    • 11.4: Connection with testing independence in contingency tables (4)
    • 11.5: Testing hypotheses about one mean (4)
    • 11.6: Testing hypotheses about the mean of paired differences (3)
    • 11.7: Testing hypotheses about the difference between two means (13)
    • 11.8: Non-parametric tests and medians (7)
    • 11.9: Tests for one or two standard deviations (4)
    • 11.10: The relationship between tests and confidence intervals (1)
    • 11.11: t-tests and ANOVA: correspondences and pitfalls of t-testing in real investigations (1)
    • 11.12: The rejection region approach to hypothesis testing (3)
    • 11.13: Sample size, statistical significance, practical importance and effect size (2)
    • 11: Active Examples (3)

  • Chapter 12: More on Probability, Random Variables and Distributions
    • 12.1: Foundations for probability (2)
    • 12.2: Probability rules (2)
    • 12.3: Independence and conditional probability (14)
    • 12.4: Using conditional probabilities (6)
    • 12.5: Bayes' theorem (10)
    • 12.6: Continuous distributions (4)
    • 12.7: A very special process: the Poisson (5)
    • 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 (5)
    • 13.3: Means and variances of linear combinations of random variables
    • 13.4: Linear combinations of normal random variables (16)
    • 13.5: Sums of some other independent random variables
    • 13.6: The sample mean and the central limit theorem (3)
    • 13.7: Combining 'errors'
    • 13: Active Examples

  • Chapter 14: Some Further Data Situations
    • 14.1: Binary logistic regression (4)
    • 14.2: Failure and survival data (8)
    • 14: Active Examples

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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AE - Active Example


Question Availability Color Key
BLACK questions are available now
GRAY questions are under development


Group Quantity Questions
Chapter 1: Thinking Statistically
1 0  
Chapter 2: Gathering and Preparing Useful Data
2.AE 1 010
2.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
3.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 Summaries and Inferential Concepts
4.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
5.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
6.AE 4 012 024 501.XP 502.XP
6.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
7.AE 1 501.XP
7.E 35 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 036 037 038 039
Chapter 8: Analysis of Variance: Categorical Predictors, Continuous Response
8.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 Quantitative Variables
9.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 and Quantitative Variables
10.AE 2 011 012
10.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 in One and Two Samples
11.AE 3 009 023 501.XP
11.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
12.E 43 001 002 003 004 005 006 007 008 009 010 011 012 013 014 015 016 017 018 019 020 021 022 023 024 025 026 027 028 029 030 031 032 033 034 035 036 037 038 039 040 041 042 043
Chapter 13: Sums and Differences of Random Variables
13.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 14: Some Further Data Situations
14.E 12 001 002 003 004 005 006 007 008 009 010 011 012
Total 541