A First Course in Statistics, 12th Edition

A First Course in Statistics, 12th Edition

by James T. McClave, Terry T. Sincich
Released January 2016
Publisher(s): Pearson
ISBN: 9780136759089

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Book description

For courses in introductory statistics.

A Contemporary Classic Classic, yet contemporary; theoretical, yet applied—McClave & Sincich’s A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. This new edition is extensively revised with an eye on clearer, more concise language throughout the text and in the exercises.

Ideal for one- or two-semester courses in introductory statistics, this text assumes a mathematical background of basic algebra.

Flexibility is built in for instructors who teach a more advanced course, with optional footnotes about calculus and the underlying theory.

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Within its structured environment, students practice what they learn, test their understanding, and pursue a personalized study plan that helps them absorb course material and understand difficult concepts. For this edition, MyStatLab offers 30% new and updated exercises.

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Table of contents

  1. Available in MyStatLabTM for Your Introductory Statistics Courses
  2. Applet Correlation
  3. A First Course in Statistics
  4. A First Course in Statistics
  5. Contents
  6. Preface
    1. New in the 12th Edition
    2. Content-Specific Changes to This Edition
    3. Hallmark Strengths
    4. Get the most out of MyStatLab™
    5. Resources for Success
    6. Reviewers of Previous Editions
    7. Other Contributors
  7. Applications Index
  8. 1 Statistics, Data, and Statistical Thinking
    1. Contents
    2. Where We’re Going
    3. 1.1 The Science of Statistics
    4. 1.2 Types of Statistical Applications
    5. 1.3 Fundamental Elements of Statistics
      1. Problem
      2. Problem
      3. Problem
    6. 1.4 Types of Data
      1. Problem
    7. 1.5 Collecting Data: Sampling and Related Issues
      1. Problem
    8. 1.6 The Role of Statistics in Critical Thinking and Ethics
      1. Problem
      2. Problem
    9. Chapter Notes
      1. Key Terms
      2. Key Ideas
        1. Types of Statistical Applications
          1. Descriptive
          2. Inferential
        2. Types of Data
        3. Data Collection Methods
        4. Types of Random Samples
        5. Problems with Nonrandom Samples
      3. Exercises 1.1–1.36
        1. Understanding the Principles
        2. Applet Exercise 1.1
        3. Applet Exercise 1.2
        4. Applying the Concepts—Basic
        5. Applying the Concepts–Intermediate
        6. Applying the Concepts—Advanced
        7. Critical Thinking Challenges
      4. References
  9. 2 Methods for Describing Sets of Data
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 2.1 Describing Qualitative Data
      1. Problem
      2. Exercises 2.1–2.24
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    5. 2.2 Graphical Methods for Describing Quantitative Data
      1. Dot Plots
      2. Stem-and-Leaf Display
      3. Histograms
        1. Problem
        2. Exercises 2.25–2.48
          1. Understanding the Principles
          2. Learning the Mechanics
          3. Applying the Concepts—Basic
          4. Applying the Concepts—Intermediate
          5. Applying the Concepts—Advanced
    6. 2.3 Numerical Measures of Central Tendency
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Problem
      6. Problem
      7. Exercises 2.49–2.72
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 2.1
        4. Applet Exercise 2.2
        5. Applet Exercise 2.3
        6. Applying the Concepts—Basic
        7. Applying the Concepts—Intermediate
        8. Applying the Concepts—Advanced
    7. 2.4 Numerical Measures of Variability
      1. Problem
      2. Problem
      3. Exercises 2.73–2.92
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 2.4
        4. Applet Exercise 2.5
        5. Applet Exercise 2.6
        6. Applying the Concepts—Basic
        7. Applying the Concepts—Intermediate
    8. 2.5 Using the Mean and Standard Deviation to Describe Data
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 2.93–2.113
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    9. 2.6 Numerical Measures of Relative Standing
      1. Problem
      2. Problem
      3. Exercises 2.114–2.131
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    10. 2.7 Methods for Detecting Outliers: Box Plots and z-Scores
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 2.132–2.153
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 2.7
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
        6. Applying the Concepts—Advanced
    11. 2.8 Graphing Bivariate Relationships (Optional)
      1. Problem
      2. Exercises 2.154–2.169
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    12. 2.9 Distorting the Truth with Descriptive Statistics
      1. Graphical Distortions
      2. Misleading Numerical Descriptive Statistics
        1. Problem
        2. Problem
        3. Exercises 2.170–2.173
          1. Applying the Concepts—Intermediate
    13. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Describing Qualitative Data
        2. Graphing Quantitative Data
        3. Rules for Describing Quantitative Data
        4. Rules for Detecting Quantitative Outliers
        5. Guide to Selecting the Data Description Method
      4. Supplementary Exercises 2.174–2.208
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
      5. References
      6. Using Technology MINITAB: Describing Data
        1. Graphing Data
        2. Numerical Descriptive Statistics
        3. TI-83/TI–84 Plus Graphing Calculator: Describing Data
          1. Histogram from Raw Data
          2. Histogram from a Frequency Table
          3. One-Variable Descriptive Statistics
          4. Sorting Data (to Find the Mode)
          5. Box Plot
          6. Scatterplots
  10. 3 Probability
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 3.1 Events, Sample Spaces, and Probability
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Problem
      6. Problem
      7. Problem
      8. Exercises 3.1–3.37
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 3.1
        4. Applet Exercise 3.2
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    5. 3.2 Unions and Intersections
      1. Problem
      2. Look Back
      3. Problem
    6. 3.3 Complementary Events
      1. Problem
    7. 3.4 The Additive Rule and Mutually Exclusive Events
      1. Problem
      2. Problem
      3. Exercises 3.38–3.67
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 3.3
        4. Applet Exercise 3.4
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    8. 3.5 Conditional Probability
      1. Problem
      2. Problem
      3. Problem
    9. 3.6 The Multiplicative Rule and Independent Events
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Statistics in Action Revisited The Probability of Winning Cash 3 or Play 4
      6. Exercises 3.68–3.103
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 3.5
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
        6. Applying the Concepts—Advanced
    10. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Probability Rules for k Sample Points, S1,S2,S3,…,Sk
        2. Combinations Rule
      4. Guide to Selecting Probability Rules
      5. Supplementary Exercises 3.104–3.146
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 3.6
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
        6. Applying the Concepts—Advanced
        7. Critical Thinking Challenges
      6. References
  11. 4 Random Variables and Probability Distributions
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 4.1 Two Types of Random Variables
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 4.1–4.16
        1. Understanding the Principles
        2. Applying the Concepts—Basic
        3. Applying the Concepts—Intermediate
    5. 4.2 Probability Distributions for Discrete Random Variables
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Problem
      6. Exercises 4.17–4.47
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 4.1
        4. Applet Exercise 4.2
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
    6. 4.3 The Binomial Random Variable
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Using Tables and Technology for Binomial Probabilities
        1. Problem
      6. Exercises 4.48–4.72
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 4.3
        4. Applet Exercise 4.4
        5. Applet Exercise 4.5
        6. Applying the Concepts—Basic
        7. Apply the Concepts—Intermediate
        8. Applying the Concepts—Advanced
    7. 4.4 Probability Distributions for Continuous Random Variables
      1. Problem
    8. 4.5 The Normal Distribution
      1. Problem
      2. Problem
      3. Problem
      4. Problem
      5. Problem
      6. Problem
      7. Problem
      8. Problem
      9. Problem
      10. Exercises 4.73–4.102
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 4.6
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
      11. Applying the Concepts—Advanced
    9. 4.6 Descriptive Methods for Assessing Normality
      1. Problem
      2. Statistics in Action Revisited Assessing whether the Normal Distribution Is Appropriate for Modeling the Super Weapon Hit Data
      3. Exercises 4.103–4.124
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
      4. 4.7 Approximating a Binomial Distribution with a Normal Distribution (Optional)
        1. Problem
      5. Exercises 4.125–4.142
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
      6. 4.8 Sampling Distributions
        1. Problem
        2. Problem
      7. Exercises 4.143–4.151
        1. Understanding the Principles
        2. Learning the Mechanics
      8. 4.9 The Sampling Distribution of x¯ and the Central Limit Theorem
        1. Problem
        2. Problem
        3. Problem
      9. Exercises 4.152–4.175
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 4.7
        4. Applet Exercise 4.8
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    10. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Properties of Discrete Probability Distributions
        2. Properties of Continuous Probability Distributions
        3. Methods for Assessing Normality
        4. Normal Approximation to Binomial
      4. Key Formulas
      5. Guide to Selecting a Probability Distribution
      6. Generating the Sampling Distribution of x ¯
      7. Supplementary Exercises 4.176–4.220
        1. Understanding the Principles
        2. Apply the Concepts–Basic
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
      8. References
      9. Using Technology MINITAB: Binomial Probabilities, Normal Probability, and Simulated Sampling Distribution
        1. Binomial Probabilites
        2. Normal Probabilities
        3. Normal Probability Plot
        4. TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables, Binomial, and Normal Probabilities
          1. Calculating the Mean and Standard Deviation of a Discrete Random Variable
          2. Calculating Binomial Probabilities
            1. I. P(x=k)
            2. II. P(x≤k)
          3. III. P(x<k),P(x>k),P(x≥k)
          4. Graphing the Area under the Standard Normal Curve
          5. Finding Normal Probabilities without a Graph
            1. Example
          6. Finding Normal Probabilities with a Graph
          7. Example
          8. Graphing a Normal Probability Plot
          9. Simulating a Sampling Distribution
  12. 5 Inferences Based on a Single Sample Estimation with Confidence Intervals
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 5.1 Identifying and Estimating the Target Parameter
    5. 5.2 Confidence Interval for a Population Mean: Normal (z) Statistic
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 5.1–5.28
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 5.1
        4. Applet Exercise 5.2
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    6. 5.3 Confidence Interval for a Population Mean: Student’s t-Statistic
      1. Problem 1
      2. Solution to Problem 1
      3. Problem 2
      4. Solution to Problem 2
        1. Problem
        2. Problem
      5. Statistics in Action Revisited Estimating the Mean Overpayment
      6. Exercises 5.29–5.51
        1. Understanding the Principles
        2. Applet Exercise 5.3
        3. Applet Exercise 5.4
        4. Learning the Mechanics
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    7. 5.4 Large-Sample Confidence Interval for a Population Proportion
      1. Problem
      2. Problem
      3. Look Ahead
      4. Problem
      5. Exercises 5.52–5.73
        1. Understanding the Principles
        2. Applet Exercise 5.5
        3. Applet Exercise 5.6
        4. Learning the Mechanics
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    8. 5.5 Determining the Sample Size
      1. Estimating a Population Mean
        1. Problem
      2. Estimating a Population Proportion
        1. Problem
      3. Exercises 5.74–5.98
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    9. 5.6 Confidence Interval for a Population Variance (Optional)
      1. Problem
      2. Problem
      3. Exercises 5.99–5.117
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basics
        4. Applying the Concepts—Intermediate
    10. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Population Parameters, Estimators, & Standard Errors
        2. Determining the Sample Size n:
        3. Key Words for Identifying the Target Parameter:
        4. Commonly Used z-values for a Large-Sample Confidence Interval for μ or p:
        5. Illustrating the Notion of “95% Confidence”
      4. Guide to Forming a Confidence Interval
      5. Supplementary Exercises 5.118–5.152
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
      6. References
  13. 6 Inferences Based on a Single Sample Tests of Hypothesis
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 6.1 The Elements of a Test of Hypothesis
    5. 6.2 Formulating Hypotheses and Setting Up the Rejection Region
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 6.1–6.21
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 6.1
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
        6. Applying the Concepts—Advanced
    6. 6.3 Observed Significance Levels: p-Values
      1. Problem
      2. Exercises 6.22–6.30
        1. Learning the Mechanics
    7. 6.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic
      1. Problem
      2. Problem
      3. Problem
      4. Exercises 6.31–6.50
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 6.2
        4. Applet Exercise 6.3
        5. Applet Exercise 6.4
        6. Applying the Concepts—Basic
        7. Applying the Concepts—Intermediate
        8. Applying the Concepts—Advanced
    8. 6.5 Test of Hypothesis about a Population Mean: Student’s t-Statistic
      1. Problem
      2. Problem
      3. Exercises 6.51–6.72
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    9. 6.6 Large-Sample Test of Hypothesis about a Population Proportion
      1. Problem
      2. Problem
      3. Small samples
      4. Exercises 6.73–6.93
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 6.5
        4. Applet Exercise 6.6
        5. Applying the Concepts—Basic
        6. Applying the Concepts—Intermediate
        7. Applying the Concepts—Advanced
    10. 6.7 Test of Hypothesis about a Population Variance (Optional)
      1. Problem
      2. Problem
      3. Exercises 6.94–6.114
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    11. 6.8 A Nonparametric Test about a Population Median (Optional)
      1. Problem
      2. Exercises 6.115–6.131
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
    12. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Key Words for Identifying the Target Parameter
        2. Elements of a Hypothesis Test
        3. Forms of Alternative Hypothesis
        4. Using p-Values to Decide
      4. Guide to Selecting a One-Sample Hypothesis Test
      5. Supplementary Exercises 6.132–6.169
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenges
      6. References
  14. 7 Comparing Population Means
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 7.1 Identifying the Target Parameter
    5. 7.2 Comparing Two Population Means: Independent Sampling
      1. Large Samples
        1. Problem
        2. Problem
        3. Problem
      2. Small Samples
        1. Problem
        2. Exercises 7.1–7.28
          1. Understanding the Principles
          2. Learning the Mechanics
          3. Applying the Concepts—Basic
          4. Applying the Concepts—Intermediate
          5. Applying the Concepts—Advanced
    6. 7.3 Comparing Two Population Means: Paired Difference Experiments
      1. Problem
      2. Exercises 7.29–7.52
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    7. 7.4 Determining the Sample Size
      1. Problem
      2. Problem
      3. Exercises 7.53–7.65
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
    8. 7.5 A Nonparametric Test for Comparing Two Populations: Independent Samples (Optional)
      1. Problem
      2. Exercises 7.66–7.85
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts-Intermediate
    9. 7.6 A Nonparametric Test for Comparing Two Populations: Paired Difference Experiment (Optional)
      1. Problem
      2. Exercises 7.86–7.102
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    10. 7.7 Comparing Three or More Population Means: Analysis of Variance (Optional)
      1. Problem
      2. Problem
      3. Exercises 7.103–7.121
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    11. Chapter Notes
      1. Key Terms
      2. Key Symbols
      3. Key Ideas
        1. Key Words for Identifying the Target Parameter
        2. Determining the Sample Size
        3. Conditions Required for Inferences about μ1−μ2
          1. Large samples:
          2. Small samples:
        4. *Conditions Required for ANOVA
          1. Large or small samples:
        5. Conditions Required for Inferences about μd
          1. Large samples:
          2. Small samples:
        6. Using a Confidence Interval for (μ1−μ2) to Determine whether a Difference Exists
      4. Guide to Comparing Population Means
      5. Supplementary Exercises 7.122–7.147
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
    12. References
  15. 8 Comparing Population Proportions
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 8.1 Comparing Two Population Proportions: Independent Sampling
      1. Problem
      2. Problem
      3. Exercises 8.1–8.23
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    5. 8.2 Determining the Sample Size
      1. Problem
      2. Exercises 8.24–8.33
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
    6. 8.3 Testing Category Probabilities: Multinomial Experiment
      1. Problem
      2. Problem
      3. Exercises 8.34–8.53
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    7. 8.4 Testing Categorical Probabilities: Two-Way (Contingency) Table
      1. Problem
      2. Contingency Tables with Fixed Marginals
        1. Exercises 8.54–8.78
          1. Understanding the Principles
          2. Learning the Mechanics
          3. Applying the Concepts—Basic
          4. Applying the Concepts—Intermediate
          5. Applying the Concepts—Advanced
    8. Chapter Notes
      1. Key Terms
      2. Key Symbols/Notation
      3. Key Ideas
        1. Multinomial Data
        2. Properties of a Multinomial Experiment
        3. One-Way Table
        4. Two-Way (Contingency) Table
        5. Chi-Square (χ2) Statistic
        6. Chi-square tests for independence
        7. Conditions Required for Valid χ2 Tests
      4. Categorical Data Analysis Guide
      5. Supplementary Exercises 8.79–8.107
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
      6. References
  16. 9 Simple Linear Regression
    1. Contents
    2. Where We’ve Been
    3. Where We’re Going
    4. 9.1 Probabilistic Models
      1. Problem
      2. Exercises 9.1–9.14
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
    5. 9.2 Fitting the Model: The Least Squares Approach
      1. Problem
      2. Exercises 9.15–9.36
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applet Exercise 9.1
        4. Applying the Concepts—Basic
        5. Applying the Concepts—Intermediate
        6. Applying the Concepts—Advanced
    6. 9.3 Model Assumptions
      1. Problem
      2. Exercises 9.37–9.52
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    7. 9.4 Assessing the Utility of the Model: Making Inferences about the Slope β1
      1. Problem
      2. Exercises 9.53–9.76
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    8. 9.5 The Coefficients of Correlation and Determination
      1. Coefficient of Correlation
        1. Problem
      2. Coefficient of Determination
        1. Problem
        2. Exercises 9.77–9.100
          1. Understanding the Principles
          2. Learning the Mechanics
          3. Applet Exercise 9.2
          4. Applying the Concepts—Basic
          5. Applying the Concepts—Intermediate
          6. Applying the Concepts—Advanced
    9. 9.6 Using the Model for Estimation and Prediction
      1. Problem
      2. Problem
      3. Exercises 9.99–9.119
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
    10. 9.7 A Complete Example
      1. Exercises 9.120–9.123
        1. Applying the Concepts—Intermediate
    11. 9.8 A Nonparametric Test for Correlation (Optional)
      1. Problem
      2. Exercises 9.124—9.139
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
    12. Chapter Notes
      1. Key Terms
      2. Key Symbols/Notation
      3. Key Ideas
        1. Simple Linear Regression Variables
        2. Method of least squares properties
        3. First-order (straight-line) model
        4. Practical interpretation of y-intercept
        5. Practical interpretation of slope
        6. Coefficient of correlation, r
        7. Coefficient of determination, r2
        8. Practical interpretation of model standard deviation s
        9. Comparing Intervals in Step 5
          1. Nonparametric Test for Rank Correlation
      4. Key Formulas
      5. Guide to Simple Linear Regression
      6. Supplementary Exercises 9.140–9.163
        1. Understanding the Principles
        2. Learning the Mechanics
        3. Applying the Concepts—Basic
        4. Applying the Concepts—Intermediate
        5. Applying the Concepts—Advanced
        6. Critical Thinking Challenge
      7. References
  17. Appendix A: Summation Notation
    1. Problem
    2. Problem
    3. Problem
  18. Appendix B: Tables
  19. Appendix C: Calculation Formulas for Analysis of Variance (Independent Sampling)
  20. Short Answers to Selected Odd Exercises
  21. Index
  22. Photo Credits
    1. Chapter 1
    2. Chapter 2
    3. Chapter 3
    4. Chapter 4
    5. Chapter 5
    6. Chapter 6
    7. Chapter 7
    8. Chapter 8
    9. Chapter 9
  23. Chapter 9
  24. Selected Formulas

Product information

  • Title: A First Course in Statistics, 12th Edition
  • Author(s): James T. McClave, Terry T. Sincich
  • Release date: January 2016
  • Publisher(s): Pearson
  • ISBN: 9780136759089