The Practice of Statistics in the Life Sciences 3rd edition

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Brigitte Baldi and David S. Moore
Publisher: W. H. Freeman

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  • Chapter 1: Picturing Distributions with Graphs
    • 1.1: Individuals and variables
    • 1.2: Categorical variables: pie charts and bar graphs
    • 1.3: Quantitative variables: histograms
    • 1.4: Interpreting histograms
    • 1.5: Quantitative variables: stemplots and dotplots
    • 1.6: Time plots
    • 1: Check Your Skills
    • 1: Exercises (59)

  • Chapter 2: Describing Distributions with Numbers
    • 2.1: Measuring center: the mean
    • 2.2: Measuring center: the median
    • 2.3: Comparing the mean and the median
    • 2.4: Measuring spread: the quartiles
    • 2.5: The five-number summary and boxplots
    • 2.6: Spotting suspected outliers
    • 2.7: Measuring spread: the standard deviation
    • 2.8: Choosing measures of center and spread
    • 2.9: Using technology
    • 2.10: Organizing a statistical problem
    • 2: Check Your Skills
    • 2: Exercises (69)

  • Chapter 3: Scatterplots and Correlation
    • 3.1: Explanatory and response variables
    • 3.2: Displaying relationships: scatterplots
    • 3.3: Interpreting scatterplots
    • 3.4: Adding categorical variables to scatterplots
    • 3.5: Measuring linear association: correlation
    • 3.6: Facts about correlation
    • 3: Check Your Skills
    • 3: Exercises (10)

  • Chapter 4: Regression
    • 4.1: The least-squares regression line
    • 4.2: Using technology
    • 4.3: Facts about least-squares regression
    • 4.4: Outliers and influential observations
    • 4.5: Cautions about correlation and regression
    • 4.6: Association does not imply causation
    • 4: Check Your Skills
    • 4: Exercises (9)

  • Chapter 5: Two-Way Tables
    • 5.1: Marginal distributions
    • 5.2: Conditional distributions
    • 5.3: Simpson's paradox
    • 5: Check Your Skills
    • 5: Exercises (6)

  • Chapter 6: Exploring Data: Part I Review
    • 6.1: Part I Summary
    • 6.2: Review Exercises
    • 6.3: Supplementary Exercises
    • 6.4: EESEE Case Studies (12)
    • 6: Exercises

  • Chapter 7: Samples and Observational Studies
    • 7.1: Observation versus experiment
    • 7.2: Sampling
    • 7.3: Sampling designs
    • 7.4: Sample surveys
    • 7.5: Cohorts and case-control studies
    • 7: Check Your Skills
    • 7: Exercises (19)

  • Chapter 8: Designing Experiments
    • 8.1: Designing experiments
    • 8.2: Randomized comparative experiments
    • 8.3: Common experimental designs
    • 8.4: Cautions about experimentation
    • 8.5: Ethics in experimentation
    • 8: Check Your Skills
    • 8: Exercises (16)

  • Chapter 9: Introducing Probability
    • 9.1: The idea of probability
    • 9.2: Probability models
    • 9.3: Probability rules
    • 9.4: Discrete probability models
    • 9.5: Continuous probability models
    • 9.6: Random variables
    • 9.7: Personal probability
    • 9.8: Risk and odds
    • 9: Check Your Skills
    • 9: Exercises (62)

  • Chapter 10: General Rules of Probability
    • 10.1: Relationships among several events
    • 10.2: Conditional probability
    • 10.3: General probability rules
    • 10.4: Tree diagrams
    • 10.5: Bayes's theorem
    • 10: Check Your Skills
    • 10: Exercises (61)

  • Chapter 11: The Normal Distributions
    • 11.1: Normal distributions
    • 11.2: The 68-95-99.7 rule
    • 11.3: The standard Normal distribution
    • 11.4: Finding Normal probabilities
    • 11.5: Using the standard Normal table
    • 11.6: Finding a value, given a probability or proportion
    • 11.7: Normal quantile plots
    • 11: Check Your Skills
    • 11: Exercises (53)

  • Chapter 12: Discrete Probability Distributions
    • 12.1: The binomial setting and binomial distributions
    • 12.2: Binomial distributions in statistical sampling
    • 12.3: Binomial probabilities
    • 12.4: Using technology
    • 12.5: Binomial mean and standard deviation
    • 12.6: The Normal approximation to binomial distributions
    • 12.7: The Poisson distributions
    • 12.8: Using technology
    • 12: Check Your Skills
    • 12: Exercises (45)

  • Chapter 13: Sampling Distributions
    • 13.1: Parameters and statistics
    • 13.2: Statistical estimation and sampling distributions
    • 13.3: The sampling distribution of
    • 13.4: The central limit theorem
    • 13.5: The sampling distribution of
    • 13.6: The law of large numbers
    • 13: Check Your Skills
    • 13: Exercises (32)

  • Chapter 14: Introduction to Interference
    • 14.1: The reasoning of statistical estimation
    • 14.2: Margin of error and confidence level
    • 14.3: Confidence intervals for the mean μ
    • 14.4: The reasoning of tests of significance
    • 14.5: Stating hypotheses
    • 14.6: P-value and statistical significance
    • 14.7: Tests for a population mean
    • 14.8: Tests from confidence intervals
    • 14: Check Your Skills
    • 14: Exercises (25)

  • Chapter 15: Inference in Practice
    • 15.1: Conditions for inference in practice
    • 15.2: How confidence intervals behave
    • 15.3: How significance tests behave
    • 15.4: Planning studies: sample size for confidence intervals
    • 15.5: Planning studies: the power of a statistical test
    • 15: Check Your Skills
    • 15: Exercises (16)

  • Chapter 16: From Exploration to Inference: Part II Review
    • 16.1: Part II Summary
    • 16.2: Review Exercises
    • 16.3: Supplementary Exercises
    • 16.4: Optional Chapters Exercises
    • 16.5: EESEE Case Studies (2)

  • Chapter 17: Inference about a Population Mean
    • 17.1: Conditions for inference
    • 17.2: The t distributions
    • 17.3: The one-sample t confidence interval
    • 17.4: The one-sample t test
    • 17.5: Using technology
    • 17.6: Matched pairs t procedures
    • 17.7: Robustness of t procedures
    • 17: Check Your Skills
    • 17: Exercises (40)

  • Chapter 18: Comparing Two Means
    • 18.1: Two-sample problems
    • 18.2: Comparing two population means
    • 18.3: Two-sample t procedures
    • 18.4: Using technology
    • 18.5: Robustness again
    • 18.6: Avoid the pooled two-sample t procedures
    • 18.7: Avoid inference about standard deviations
    • 18: Check Your Skills
    • 18: Exercises (44)

  • Chapter 19: Inference about a Population Proportion
    • 19.1: The sample proportion
    • 19.2: Large-sample confidence intervals for a proportion
    • 19.3: Accurate confidence intervals for a proportion
    • 19.4: Choosing the sample size
    • 19.5: Significance tests for a proportion
    • 19.6: Using technology
    • 19: Check Your Skills
    • 19: Exercises (32)

  • Chapter 20: Comparing Two Proportions
    • 20.1: Two-sample problems: proportions
    • 20.2: The sampling distribution of a difference between proportions
    • 20.3: Large-sample confidence intervals for comparing proportions
    • 20.4: Accurate confidence intervals for comparing proportions
    • 20.5: Significance tests for comparing proportions
    • 20.6: Relative risk and odds ratio
    • 20: Check Your Skills
    • 20: Exercises (24)

  • Chapter 21: The Chi-Square Test for Goodness of Fit
    • 21.1: Hypotheses for goodness of fit
    • 21.2: The chi-square test for goodness of fit
    • 21.3: Using technology
    • 21.4: Interpreting chi-square results
    • 21.5: Conditions for the chi-square test
    • 21.6: The chi-square distributions
    • 21.7: The chi-square test and the one-sample z test
    • 21: Check Your Skills
    • 21: Exercises (8)

  • Chapter 22: The Chi-Square Test for Two-Way Tables
    • 22.1: Two-way tables
    • 22.2: The problem of multiple comparisons
    • 22.3: Expected counts in two-way tables
    • 22.4: The chi-square test
    • 22.5: Using technology
    • 22.6: Conditions for the chi-square test
    • 22.7: Uses of the chi-square test
    • 22.8: Using a table of critical values
    • 22.9: The chi-square test and the two-sample z test
    • 22: Check Your Skills
    • 22: Exercises (51)

  • Chapter 23: Inference for Regression
    • 23.1: Conditions for regression inference
    • 23.2: Estimating the parameters
    • 23.3: Using technology
    • 23.4: Testing the hypothesis of no linear relationship
    • 23.5: Testing lack of correlation
    • 23.6: Confidence intervals for the regression slope
    • 23.7: Inference about prediction
    • 23.8: Checking the conditions for inference
    • 23: Check Your Skills
    • 23: Exercises (70)

  • Chapter 24: One-Way Analysis of Variance: Comparing Several Means
    • 24.1: Comparing several means
    • 24.2: The analysis of variance F test
    • 24.3: Using technology
    • 24.4: The idea of analysis of variance
    • 24.5: Conditions for ANOVA
    • 24.6: F distributions and degrees of freedom
    • 24.7: The one-way ANOVA and the pooled two-sample t test
    • 24.8: Details of ANOVA calculations
    • 24: Check Your Skills
    • 24: Exercises (47)

  • Chapter 25: Statistical Inference: Part III Review
    • 25.1: Part III Summary
    • 25.2: Review Exercises
    • 25.3: Supplementary Exercises
    • 25.4: EESEE Case Studies (7)

  • Chapter 26: More about Analysis of Variance: Follow-up Tests and Two-Way ANOVA
    • 26.1: Beyond one-way ANOVA
    • 26.2: Follow-up analysis: Tukey's pairwise multiple comparisons
    • 26.3: Follow-up analysis: contrasts
    • 26.4: Two-way ANOVA: conditions, main effects, and interaction
    • 26.5: Inference for two-way ANOVA
    • 26.6: Some details of two-way ANOVA

  • Chapter 27: Nonparametric Tests
    • 27.1: Comparing two samples: the Wilcoxon rank sum test
    • 27.2: Matched pairs: the Wilcoxon signed rank test
    • 27.3: Comparing several samples: the Kruskal-Wallis test

  • Chapter 28: Multiple and Logistic Regression
    • 28.1: Parallel regression lines
    • 28.2: Estimating parameters
    • 28.3: Using technology
    • 28.4: Conditions for inference
    • 28.5: Inference for multiple regression
    • 28.6: Interaction
    • 28.7: A case study for multiple regression
    • 28.8: Logistic regression
    • 28.9: Inference for logistic regression


Features
  • Every WebAssign question links to applicable chapters in a fully integrated eBook.
  • Learning Curve adaptive quizzing available for every chapter.
  • StatTutors provide multimedia tutorials with built-in assessments that explore important statistics concepts and procedures.
  • Video Technology Manuals provide brief instructions for using specific statistical software (over 50 topics/videos per software) and are available for TI-83/84 calculators, JMP, Excel, Minitab, SPSS, R, and RCmdr.
  • Statistical Videos consist of StatClips, StatClips Examples, and Statistically Speaking "Snapshots," including animated lecture videos, whiteboard lessons, and documentary-style footage that illustrate key statistical concepts and help students visualize statistics in real-world scenarios.
  • Associated data files from the textbook are available to use for appropriate exercises, formatted for TI-83/84 calculators, JMP, Excel, Minitab, SPSS, R, and RCmdr.
  • Downloadable test banks and practice quizzes for each chapter.
  • Book specific PowerPoint lecture slides and iClicker slides.
  • Instructor and student solution manuals.


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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GRAY questions are under development


Group Quantity Questions
Chapter 1: Picturing Distributions with Graphs
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Chapter 2: Describing Distributions with Numbers
2.E 69 010 019 022 028 033 034 036 037 039 040 501.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 521.XP 522.XP 523.XP 524.XP 525.XP 526.XP 527.XP 528.XP 529.XP 530.XP 531.XP 532.XP 533.XP 534.XP 535.XP 536.XP 537.XP 538.XP 539.XP 540.XP 541.XP 542.XP 543.XP 544.XP 545.XP 546.XP 547.XP 548.XP 549.XP 550.XP 551.XP 552.XP 553.XP 554.XP 555.XP 556.XP 557.XP 558.XP 559.XP
Chapter 3: Scatterplots and Correlation
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Chapter 4: Regression
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Chapter 5: Two-Way Tables
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Chapter 6: Exploring Data: Part I Review
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Chapter 7: Samples and Observational Studies
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Chapter 8: Designing Experiments
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Chapter 9: Introducing Probability
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Chapter 10: General Rules of Probability
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10.e 1 526.XP
Chapter 11: The Normal Distributions
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Chapter 12: Discrete Probability Distributions
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Chapter 13: Sampling Distributions
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Chapter 14: Introduction to Interference
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Chapter 15: Inference in Practice
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Chapter 16: From Exploration to Inference: Part II Review
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Chapter 17: Inference about a Population Mean
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Chapter 18: Comparing Two Means
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Chapter 19: Inference about a Population Proportion
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Chapter 20: Comparing Two Proportions
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Chapter 21: The Chi-Square Test for Goodness of Fit
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Chapter 22: The Chi-Square Test for Two-Way Tables
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Chapter 23: Inference for Regression
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Chapter 24: One-Way Analysis of Variance: Comparing Several Means
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Chapter 25: Statistical Inference: Part III Review
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Chapter 26: More about Analysis of Variance: Follow-up Tests and Two-Way ANOVA
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Chapter 27: Nonparametric Tests
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Chapter 28: Multiple and Logistic Regression
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Total 819