Home Page Icon
Home Page
Table of Contents for
A First Course in Statistics
Close
A First Course in Statistics
by Terry T. Sincich, James T. McClave
A First Course in Statistics, 12th Edition
Available in MyStatLabTM for Your Introductory Statistics Courses
Applet Correlation
A First Course in Statistics
A First Course in Statistics
Contents
Preface
New in the 12th Edition
Content-Specific Changes to This Edition
Hallmark Strengths
Get the most out of MyStatLab™
Resources for Success
Reviewers of Previous Editions
Other Contributors
Applications Index
1 Statistics, Data, and Statistical Thinking
Contents
Where We’re Going
1.1 The Science of Statistics
1.2 Types of Statistical Applications
1.3 Fundamental Elements of Statistics
Problem
Problem
Problem
1.4 Types of Data
Problem
1.5 Collecting Data: Sampling and Related Issues
Problem
1.6 The Role of Statistics in Critical Thinking and Ethics
Problem
Problem
Chapter Notes
Key Terms
Key Ideas
Types of Statistical Applications
Descriptive
Inferential
Types of Data
Data Collection Methods
Types of Random Samples
Problems with Nonrandom Samples
Exercises 1.1–1.36
Understanding the Principles
Applet Exercise 1.1
Applet Exercise 1.2
Applying the Concepts—Basic
Applying the Concepts–Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
2 Methods for Describing Sets of Data
Contents
Where We’ve Been
Where We’re Going
2.1 Describing Qualitative Data
Problem
Exercises 2.1–2.24
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.2 Graphical Methods for Describing Quantitative Data
Dot Plots
Stem-and-Leaf Display
Histograms
Problem
Exercises 2.25–2.48
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.3 Numerical Measures of Central Tendency
Problem
Problem
Problem
Problem
Problem
Problem
Exercises 2.49––2.72
Understanding the Principles
Learning the Mechanics
Applet Exercise 2.1
Applet Exercise 2.2
Applet Exercise 2.3
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.4 Numerical Measures of Variability
Problem
Problem
Exercises 2.73–2.92
Understanding the Principles
Learning the Mechanics
Applet Exercise 2.4
Applet Exercise 2.5
Applet Exercise 2.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
2.5 Using the Mean and Standard Deviation to Describe Data
Problem
Problem
Problem
Exercises 2.93––2.113
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.6 Numerical Measures of Relative Standing
Problem
Problem
Exercises 2.114–2.131
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.7 Methods for Detecting Outliers: Box Plots and z-Scores
Problem
Problem
Problem
Exercises 2.132––2.153
Understanding the Principles
Learning the Mechanics
Applet Exercise 2.7
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.8 Graphing Bivariate Relationships (Optional)
Problem
Exercises 2.154––2.169
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.9 Distorting the Truth with Descriptive Statistics
Graphical Distortions
Misleading Numerical Descriptive Statistics
Problem
Problem
Exercises 2.170–2.173
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Describing Qualitative Data
Graphing Quantitative Data
Rules for Describing Quantitative Data
Rules for Detecting Quantitative Outliers
Guide to Selecting the Data Description Method
Supplementary Exercises 2.174–2.208
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Using Technology MINITAB: Describing Data
Graphing Data
Numerical Descriptive Statistics
TI-83/TI–84 Plus Graphing Calculator: Describing Data
Histogram from Raw Data
Histogram from a Frequency Table
One-Variable Descriptive Statistics
Sorting Data (to Find the Mode)
Box Plot
Scatterplots
3 Probability
Contents
Where We’ve Been
Where We’re Going
3.1 Events, Sample Spaces, and Probability
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Exercises 3.1–3.37
Understanding the Principles
Learning the Mechanics
Applet Exercise 3.1
Applet Exercise 3.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
3.2 Unions and Intersections
Problem
Look Back
Problem
3.3 Complementary Events
Problem
3.4 The Additive Rule and Mutually Exclusive Events
Problem
Problem
Exercises 3.38–3.67
Understanding the Principles
Learning the Mechanics
Applet Exercise 3.3
Applet Exercise 3.4
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
3.5 Conditional Probability
Problem
Problem
Problem
3.6 The Multiplicative Rule and Independent Events
Problem
Problem
Problem
Problem
Statistics in Action Revisited The Probability of Winning Cash 3 or Play 4
Exercises 3.68–3.103
Understanding the Principles
Learning the Mechanics
Applet Exercise 3.5
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Probability Rules for k Sample Points, S1,S2,S3,…,Sk
Combinations Rule
Guide to Selecting Probability Rules
Supplementary Exercises 3.104–3.146
Understanding the Principles
Learning the Mechanics
Applet Exercise 3.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
4 Random Variables and Probability Distributions
Contents
Where We’ve Been
Where We’re Going
4.1 Two Types of Random Variables
Problem
Problem
Problem
Exercises 4.1–4.16
Understanding the Principles
Applying the Concepts—Basic
Applying the Concepts—Intermediate
4.2 Probability Distributions for Discrete Random Variables
Problem
Problem
Problem
Problem
Problem
Exercises 4.17–4.47
Understanding the Principles
Learning the Mechanics
Applet Exercise 4.1
Applet Exercise 4.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
4.3 The Binomial Random Variable
Problem
Problem
Problem
Problem
Using Tables and Technology for Binomial Probabilities
Problem
Exercises 4.48–4.72
Understanding the Principles
Learning the Mechanics
Applet Exercise 4.3
Applet Exercise 4.4
Applet Exercise 4.5
Applying the Concepts—Basic
Apply the Concepts—Intermediate
Applying the Concepts—Advanced
4.4 Probability Distributions for Continuous Random Variables
Problem
4.5 The Normal Distribution
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Exercises 4.73–4.102
Understanding the Principles
Learning the Mechanics
Applet Exercise 4.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.6 Descriptive Methods for Assessing Normality
Problem
Statistics in Action Revisited Assessing whether the Normal Distribution Is Appropriate for Modeling the Super Weapon Hit Data
Exercises 4.103–4.124
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.7 Approximating a Binomial Distribution with a Normal Distribution (Optional)
Problem
Exercises 4.125–4.142
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.8 Sampling Distributions
Problem
Problem
Exercises 4.143–4.151
Understanding the Principles
Learning the Mechanics
4.9 The Sampling Distribution of x¯ and the Central Limit Theorem
Problem
Problem
Problem
Exercises 4.152–4.175
Understanding the Principles
Learning the Mechanics
Applet Exercise 4.7
Applet Exercise 4.8
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Properties of Discrete Probability Distributions
Properties of Continuous Probability Distributions
Methods for Assessing Normality
Normal Approximation to Binomial
Key Formulas
Guide to Selecting a Probability Distribution
Generating the Sampling Distribution of x ¯
Supplementary Exercises 4.176–4.220
Understanding the Principles
Apply the Concepts–Basic
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Using Technology MINITAB: Binomial Probabilities, Normal Probability, and Simulated Sampling Distribution
Binomial Probabilites
Normal Probabilities
Normal Probability Plot
TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables, Binomial, and Normal Probabilities
Calculating the Mean and Standard Deviation of a Discrete Random Variable
Calculating Binomial Probabilities
I. P(x=k)
II. P(x≤k)
III. P(x<k),P(x>k),P(x≥k)
Graphing the Area under the Standard Normal Curve
Finding Normal Probabilities without a Graph
Example
Finding Normal Probabilities with a Graph
Example
Graphing a Normal Probability Plot
Simulating a Sampling Distribution
5 Inferences Based on a Single Sample Estimation with Confidence Intervals
Contents
Where We’ve Been
Where We’re Going
5.1 Identifying and Estimating the Target Parameter
5.2 Confidence Interval for a Population Mean: Normal (z) Statistic
Problem
Problem
Problem
Exercises 5.1–5.28
Understanding the Principles
Learning the Mechanics
Applet Exercise 5.1
Applet Exercise 5.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.3 Confidence Interval for a Population Mean: Student’s t-Statistic Confidence Interval for a Population Mean: Student’s t-Statistic
Problem 1
Solution to Problem 1
Problem 2
Solution to Problem 2
Problem
Problem
Statistics in Action Revisited Estimating the Mean Overpayment
Exercises 5.29–5.51
Understanding the Principles
Applet Exercise 5.3
Applet Exercise 5.4
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.4 Large-Sample Confidence Interval for a Population Proportion
Problem
Problem
Look Ahead
Problem
Exercises 5.52–5.73
Understanding the Principles
Applet Exercise 5.5
Applet Exercise 5.6
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.5 Determining the Sample Size
Estimating a Population Mean
Problem
Estimating a Population Proportion
Problem
Exercises 5.74–5.98
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.6 Confidence Interval for a Population Variance (Optional)
Problem
Problem
Exercises 5.99–5.117
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basics
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Population Parameters, Estimators, & Standard Errors
Determining the Sample Size n:
Key Words for Identifying the Target Parameter:
Commonly Used z-values for a Large-Sample Confidence Interval for μ or p:
Illustrating the Notion of “95% Confidence”
Guide to Forming a Confidence Interval
Supplementary Exercises 5.118–5.152
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
6 Inferences Based on a Single Sample Tests of Hypothesis
Contents
Where We’ve Been
Where We’re Going
6.1 The Elements of a Test of Hypothesis
6.2 Formulating Hypotheses and Setting Up the Rejection Region
Problem
Problem
Problem
Exercises 6.1–6.21
Understanding the Principles
Learning the Mechanics
Applet Exercise 6.1
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.3 Observed Significance Levels: p-Values
Problem
Exercises 6.22–6.30
Learning the Mechanics
6.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic
Problem
Problem
Problem
Exercises 6.31–6.50
Understanding the Principles
Learning the Mechanics
Applet Exercise 6.2
Applet Exercise 6.3
Applet Exercise 6.4
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.5 Test of Hypothesis about a Population Mean: Student’s t-Statistic Test of Hypothesis about a Population Mean: Student’s t-Statistic
Problem
Problem
Exercises 6.51–6.72
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.6 Large-Sample Test of Hypothesis about a Population Proportion
Problem
Problem
Small samples
Exercises 6.73–6.93
Understanding the Principles
Learning the Mechanics
Applet Exercise 6.5
Applet Exercise 6.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.7 Test of Hypothesis about a Population Variance (Optional)
Problem
Problem
Exercises 6.94–6.114
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.8 A Nonparametric Test about a Population Median (Optional)
Problem
Exercises 6.115–6.131
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Key Words for Identifying the Target Parameter
Elements of a Hypothesis Test
Forms of Alternative Hypothesis
Using p-Values to Decide
Guide to Selecting a One-Sample Hypothesis Test
Supplementary Exercises 6.132–6.169
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
7 Comparing Population Means
Contents
Where We’ve Been
Where We’re Going
7.1 Identifying the Target Parameter
7.2 Comparing Two Population Means: Independent Sampling
Large Samples
Problem
Problem
Problem
Small Samples
Problem
Exercises 7.1–7.28
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.3 Comparing Two Population Means: Paired Difference Experiments
Problem
Exercises 7.29–7.52
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.4 Determining the Sample Size
Problem
Problem
Exercises 7.53–7.65
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
7.5 A Nonparametric Test for Comparing Two Populations: Independent Samples (Optional)
Problem
Exercises 7.66–7.85
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts-Intermediate
7.6 A Nonparametric Test for Comparing Two Populations: Paired Difference Experiment (Optional)
Problem
Exercises 7.86–7.102
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.7 Comparing Three or More Population Means: Analysis of Variance (Optional)
Problem
Problem
Exercises 7.103–7.121
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Key Words for Identifying the Target Parameter
Determining the Sample Size
Conditions Required for Inferences about μ1−μ2
Large samples:
Small samples:
*Conditions Required for ANOVA
Large or small samples:
Conditions Required for Inferences about μd
Large samples:
Small samples:
Using a Confidence Interval for (μ1−μ2) to Determine whether a Difference Exists
Guide to Comparing Population Means
Supplementary Exercises 7.122–7.147
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
8 Comparing Population Proportions
Contents
Where We’ve Been
Where We’re Going
8.1 Comparing Two Population Proportions: Independent Sampling
Problem
Problem
Exercises 8.1–8.23
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
8.2 Determining the Sample Size
Problem
Exercises 8.24–8.33
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
8.3 Testing Category Probabilities: Multinomial Experiment
Problem
Problem
Exercises 8.34–8.53
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
8.4 Testing Categorical Probabilities: Two-Way (Contingency) Table
Problem
Contingency Tables with Fixed Marginals
Exercises 8.54–8.78
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols/Notation
Key Ideas
Multinomial Data
Properties of a Multinomial Experiment
One-Way Table
Two-Way (Contingency) Table
Chi-Square (χ2) Statistic
Chi-square tests for independence
Conditions Required for Valid χ2 Tests
Categorical Data Analysis Guide
Supplementary Exercises 8.79–8.107
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
9 Simple Linear Regression
Contents
Where We’ve Been
Where We’re Going
9.1 Probabilistic Models
Problem
Exercises 9.1–9.14
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
9.2 Fitting the Model: The Least Squares Approach
Problem
Exercises 9.15–9.36
Understanding the Principles
Learning the Mechanics
Applet Exercise 9.1
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.3 Model Assumptions
Problem
Exercises 9.37–9.52
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.4 Assessing the Utility of the Model: Making Inferences about the Slope β1
Problem
Exercises 9.53–9.76
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.5 The Coefficients of Correlation and Determination
Coefficient of Correlation
Problem
Coefficient of Determination
Problem
Exercises 9.77–9.100
Understanding the Principles
Learning the Mechanics
Applet Exercise 9.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.6 Using the Model for Estimation and Prediction
Problem
Problem
Exercises 9.99–9.119
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.7 A Complete Example
Exercises 9.120–9.123
Applying the Concepts—Intermediate
9.8 A Nonparametric Test for Correlation (Optional)
Problem
Exercises 9.124—9.139
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols/Notation
Key Ideas
Simple Linear Regression Variables
Method of least squares properties
First-order (straight-line) model
Practical interpretation of y-intercept
Practical interpretation of slope
Coefficient of correlation, r
Coefficient of determination, r2
Practical interpretation of model standard deviation s
Comparing Intervals in Step 5
Nonparametric Test for Rank Correlation
Key Formulas
Guide to Simple Linear Regression
Supplementary Exercises 9.140–9.163
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Appendix A: Summation Notation
Problem
Problem
Problem
Appendix B: Tables
Appendix C: Calculation Formulas for Analysis of Variance (Independent Sampling)
Short Answers to Selected Odd Exercises
Index
Photo Credits
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 9
Selected Formulas
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Selected Formulas
Contents
Available in MyStatLab
TM
for Your Introductory Statistics Courses
Applet Correlation
A First Course in Statistics
A First Course in Statistics
Contents
Preface
New in the 12th Edition
Content-Specific Changes to This Edition
Hallmark Strengths
Get the most out of MyStatLab
™
Resources for Success
Reviewers of Previous Editions
Other Contributors
Applications Index
1
Statistics, Data, and Statistical Thinking
Contents
Where We’re Going
1.1
The Science of Statistics
1.2
Types of Statistical Applications
1.3
Fundamental Elements of Statistics
Problem
Problem
Problem
1.4
Types of Data
Problem
1.5
Collecting Data: Sampling and Related Issues
Problem
1.6
The Role of Statistics in Critical Thinking and Ethics
Problem
Problem
Chapter Notes
Key Terms
Key Ideas
Types of Statistical Applications
Descriptive
Inferential
Types of Data
Data Collection Methods
Types of Random Samples
Problems with Nonrandom Samples
Exercises
1.1–1.36
Understanding the Principles
Applet Exercise
1.1
Applet Exercise
1.2
Applying the Concepts—Basic
Applying the Concepts–Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
2
Methods for Describing Sets of Data
Contents
Where We’ve Been
Where We’re Going
2.1
Describing Qualitative Data
Problem
Exercises
2.1–
2.24
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.2
Graphical Methods for Describing Quantitative Data
Dot Plots
Stem-and-Leaf Display
Histograms
Problem
Exercises
2.25–
2.48
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.3
Numerical Measures of Central Tendency
Problem
Problem
Problem
Problem
Problem
Problem
Exercises
2.49
–
2.72
Understanding the Principles
Learning the Mechanics
Applet Exercise
2.1
Applet Exercise
2.2
Applet Exercise
2.3
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.4
Numerical Measures of Variability
Problem
Problem
Exercises
2.73–2.92
Understanding the Principles
Learning the Mechanics
Applet Exercise
2.4
Applet Exercise
2.5
Applet Exercise
2.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
2.5
Using the Mean and Standard Deviation to Describe Data
Problem
Problem
Problem
Exercises
2.93
–
2.113
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.6
Numerical Measures of Relative Standing
Problem
Problem
Exercises
2.114–2.131
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.7
Methods for Detecting Outliers: Box Plots and z-Scores
Problem
Problem
Problem
Exercises
2.132
–
2.153
Understanding the Principles
Learning the Mechanics
Applet Exercise
2.7
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.8
Graphing Bivariate Relationships (Optional)
Problem
Exercises
2.154
–
2.169
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
2.9
Distorting the Truth with Descriptive Statistics
Graphical Distortions
Misleading Numerical Descriptive Statistics
Problem
Problem
Exercises
2.170
–2.173
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Describing Qualitative Data
Graphing Quantitative Data
Rules for Describing Quantitative Data
Rules for Detecting Quantitative Outliers
Guide to Selecting the Data Description Method
Supplementary Exercises
2.174–
2.208
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Using Technology MINITAB: Describing Data
Graphing Data
Numerical Descriptive Statistics
TI-83/TI–84 Plus Graphing Calculator: Describing Data
Histogram from Raw Data
Histogram from a Frequency Table
One-Variable Descriptive Statistics
Sorting Data (to Find the Mode)
Box Plot
Scatterplots
3
Probability
Contents
Where We’ve Been
Where We’re Going
3.1
Events, Sample Spaces, and Probability
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Exercises
3.1–
3.37
Understanding the Principles
Learning the Mechanics
Applet Exercise
3.1
Applet Exercise
3.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
3.2
Unions and Intersections
Problem
Look Back
Problem
3.3
Complementary Events
Problem
3.4
The Additive Rule and Mutually Exclusive Events
Problem
Problem
Exercises
3.38–
3.67
Understanding the Principles
Learning the Mechanics
Applet Exercise
3.3
Applet Exercise
3.4
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
3.5
Conditional Probability
Problem
Problem
Problem
3.6
The Multiplicative Rule and Independent Events
Problem
Problem
Problem
Problem
Statistics in Action Revisited
The Probability of Winning Cash 3 or Play 4
Exercises
3.68–
3.103
Understanding the Principles
Learning the Mechanics
Applet Exercise
3.5
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Probability Rules for k Sample Points,
S
1
,
S
2
,
S
3
,
…
,
S
k
S
1
,
S
2
,
S
3
,
…
,
S
k
Combinations Rule
Guide to Selecting Probability Rules
Supplementary Exercises
3.104–3.146
Understanding the Principles
Learning the Mechanics
Applet Exercise
3.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
4
Random Variables and Probability Distributions
Contents
Where We’ve Been
Where We’re Going
4.1
Two Types of Random Variables
Problem
Problem
Problem
Exercises
4.1–4.16
Understanding the Principles
Applying the Concepts—Basic
Applying the Concepts—Intermediate
4.2
Probability Distributions for Discrete Random Variables
Problem
Problem
Problem
Problem
Problem
Exercises
4.17–4.47
Understanding the Principles
Learning the Mechanics
Applet Exercise
4.1
Applet Exercise
4.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
4.3
The Binomial Random Variable
Problem
Problem
Problem
Problem
Using Tables and Technology for Binomial Probabilities
Problem
Exercises
4.48–4.72
Understanding the Principles
Learning the Mechanics
Applet Exercise
4.3
Applet Exercise
4.4
Applet Exercise
4.5
Applying the Concepts—Basic
Apply the Concepts—Intermediate
Applying the Concepts—Advanced
4.4
Probability Distributions for Continuous Random Variables
Problem
4.5
The Normal Distribution
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Problem
Exercises 4.73–4.102
Understanding the Principles
Learning the Mechanics
Applet Exercise
4.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.6
Descriptive Methods for Assessing Normality
Problem
Statistics in Action Revisited
Assessing whether the Normal Distribution Is Appropriate for Modeling the Super Weapon Hit Data
Exercises 4.103–4.124
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.7
Approximating a Binomial Distribution with a Normal Distribution (Optional)
Problem
Exercises
4.125–4.142
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
4.8
Sampling Distributions
Problem
Problem
Exercises
4.143–4.151
Understanding the Principles
Learning the Mechanics
4.9
The Sampling Distribution of
x
¯
x
¯
and the Central Limit Theorem
Problem
Problem
Problem
Exercises
4.152–4.175
Understanding the Principles
Learning the Mechanics
Applet Exercise
4.7
Applet Exercise
4.8
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Properties of Discrete Probability Distributions
Properties of Continuous Probability Distributions
Methods for Assessing Normality
Normal Approximation to Binomial
Key Formulas
Guide to Selecting a Probability Distribution
Generating the Sampling Distribution of
x
¯
x
¯
Supplementary Exercises
4.176–4.220
Understanding the Principles
Apply the Concepts–Basic
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Using Technology MINITAB: Binomial Probabilities, Normal Probability, and Simulated Sampling Distribution
Binomial Probabilites
Normal Probabilities
Normal Probability Plot
TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables, Binomial, and Normal Probabilities
Calculating the Mean and Standard Deviation of a Discrete Random Variable
Calculating Binomial Probabilities
I.
P
(
x
=
k
)
P
(
x
=
k
)
II.
P
(
x
≤
k
)
P
(
x
≤
k
)
III.
P
(
x
<
k
)
,
P
(
x
>
k
)
,
P
(
x
≥
k
)
P
(
x
<
k
)
,
P
(
x
>
k
)
,
P
(
x
≥
k
)
Graphing the Area under the Standard Normal Curve
Finding Normal Probabilities without a Graph
Example
Finding Normal Probabilities with a Graph
Example
Graphing a Normal Probability Plot
Simulating a Sampling Distribution
5
Inferences Based on a Single Sample
Estimation with Confidence Intervals
Contents
Where We’ve Been
Where We’re Going
5.1
Identifying and Estimating the Target Parameter
5.2
Confidence Interval for a Population Mean: Normal (z) Statistic
Problem
Problem
Problem
Exercises
5.1–5.28
Understanding the Principles
Learning the Mechanics
Applet Exercise
5.1
Applet Exercise
5.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.3
Confidence Interval for a Population Mean: Student’s t-Statistic
Problem
1
Solution to Problem
1
Problem
2
Solution to Problem
2
Problem
Problem
Statistics in Action Revisited
Estimating the Mean Overpayment
Exercises
5.29–5.51
Understanding the Principles
Applet Exercise
5.3
Applet Exercise
5.4
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.4
Large-Sample Confidence Interval for a Population Proportion
Problem
Problem
Look Ahead
Problem
Exercises
5.52–5.73
Understanding the Principles
Applet Exercise
5.5
Applet Exercise
5.6
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.5
Determining the Sample Size
Estimating a Population Mean
Problem
Estimating a Population Proportion
Problem
Exercises
5.74–5.98
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
5.6
Confidence Interval for a Population Variance (Optional)
Problem
Problem
Exercises
5.99–5.117
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basics
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Population Parameters, Estimators, & Standard Errors
Determining the Sample Size n:
Key Words for Identifying the Target Parameter:
Commonly Used z-values for a Large-Sample Confidence Interval for
μ
μ
or p:
Illustrating the Notion of “95% Confidence”
Guide to Forming a Confidence Interval
Supplementary Exercises
5.118–5.152
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
6
Inferences Based on a Single Sample
Tests of Hypothesis
Contents
Where We’ve Been
Where We’re Going
6.1
The Elements of a Test of Hypothesis
6.2
Formulating Hypotheses and Setting Up the Rejection Region
Problem
Problem
Problem
Exercises
6.1–6.21
Understanding the Principles
Learning the Mechanics
Applet Exercise
6.1
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.3
Observed Significance Levels: p-Values
Problem
Exercises
6.22–6.30
Learning the Mechanics
6.4
Test of Hypothesis about a Population Mean: Normal (z) Statistic
Problem
Problem
Problem
Exercises
6.31–6.50
Understanding the Principles
Learning the Mechanics
Applet Exercise
6.2
Applet Exercise
6.3
Applet Exercise
6.4
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.5
Test of Hypothesis about a Population Mean: Student’s t-Statistic
Problem
Problem
Exercises
6.51–6.72
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.6
Large-Sample Test of Hypothesis about a Population Proportion
Problem
Problem
Small samples
Exercises
6.73–6.93
Understanding the Principles
Learning the Mechanics
Applet Exercise
6.5
Applet Exercise
6.6
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.7
Test of Hypothesis about a Population Variance (Optional)
Problem
Problem
Exercises
6.94–6.114
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
6.8
A Nonparametric Test about a Population Median (Optional)
Problem
Exercises
6.115–6.131
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Key Words for Identifying the Target Parameter
Elements of a Hypothesis Test
Forms of Alternative Hypothesis
Using p-Values to Decide
Guide to Selecting a One-Sample Hypothesis Test
Supplementary Exercises
6.132–6.169
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenges
References
7
Comparing Population Means
Contents
Where We’ve Been
Where We’re Going
7.1
Identifying the Target Parameter
7.2
Comparing Two Population Means: Independent Sampling
Large Samples
Problem
Problem
Problem
Small Samples
Problem
Exercises 7.1–7.28
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.3
Comparing Two Population Means: Paired Difference Experiments
Problem
Exercises
7.29–7.52
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.4
Determining the Sample Size
Problem
Problem
Exercises
7.53–7.65
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
7.5
A Nonparametric Test for Comparing Two Populations: Independent Samples (Optional)
Problem
Exercises
7.66–7.85
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts-Intermediate
7.6
A Nonparametric Test for Comparing Two Populations: Paired Difference Experiment (Optional)
Problem
Exercises
7.86–7.102
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
7.7
Comparing Three or More Population Means: Analysis of Variance (Optional)
Problem
Problem
Exercises
7.103–7.121
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols
Key Ideas
Key Words for Identifying the Target Parameter
Determining the Sample Size
Conditions Required for Inferences about
μ
1
−
μ
2
μ
1
−
μ
2
Large samples:
Small samples:
*Conditions Required for ANOVA
Large or small samples:
Conditions Required for Inferences about
μ
d
μ
d
Large samples:
Small samples:
Using a Confidence Interval for
(
μ
1
−
μ
2
)
(
μ
1
−
μ
2
)
to Determine whether a Difference Exists
Guide to Comparing Population Means
Supplementary Exercises 7.122–7.147
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
8
Comparing Population Proportions
Contents
Where We’ve Been
Where We’re Going
8.1
Comparing Two Population Proportions: Independent Sampling
Problem
Problem
Exercises
8.1–8.23
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
8.2
Determining the Sample Size
Problem
Exercises
8.24–8.33
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
8.3
Testing Category Probabilities: Multinomial Experiment
Problem
Problem
Exercises
8.34–8.53
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
8.4
Testing Categorical Probabilities: Two-Way (Contingency) Table
Problem
Contingency Tables with Fixed Marginals
Exercises
8.54–
8.78
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Chapter Notes
Key Terms
Key Symbols/Notation
Key Ideas
Multinomial Data
Properties of a Multinomial Experiment
One-Way Table
Two-Way (Contingency) Table
Chi-Square
(
χ
2
)
(
χ
2
)
Statistic
Chi-square tests for independence
Conditions Required for Valid
χ
2
χ
2
Tests
Categorical Data Analysis Guide
Supplementary Exercises
8.79–
8.107
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
9
Simple Linear Regression
Contents
Where We’ve Been
Where We’re Going
9.1
Probabilistic Models
Problem
Exercises
9.1–9.14
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
9.2
Fitting the Model: The Least Squares Approach
Problem
Exercises
9.15–9.36
Understanding the Principles
Learning the Mechanics
Applet Exercise
9.1
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.3
Model Assumptions
Problem
Exercises
9.37–9.52
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.4
Assessing the Utility of the Model: Making Inferences about the Slope
β
1
β
1
Problem
Exercises
9.53–9.76
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.5
The Coefficients of Correlation and Determination
Coefficient of Correlation
Problem
Coefficient of Determination
Problem
Exercises
9.77–9.100
Understanding the Principles
Learning the Mechanics
Applet Exercise
9.2
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.6
Using the Model for Estimation and Prediction
Problem
Problem
Exercises
9.99–9.119
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
9.7
A Complete Example
Exercises
9.120–9.123
Applying the Concepts—Intermediate
9.8
A Nonparametric Test for Correlation (Optional)
Problem
Exercises
9.124—9.139
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Chapter Notes
Key Terms
Key Symbols/Notation
Key Ideas
Simple Linear Regression Variables
Method of least squares properties
First-order (straight-line) model
Practical interpretation of y-intercept
Practical interpretation of slope
Coefficient of correlation, r
Coefficient of determination,
r
2
r
2
Practical interpretation of model standard deviation s
Comparing Intervals in Step 5
Nonparametric Test for Rank Correlation
Key Formulas
Guide to Simple Linear Regression
Supplementary Exercises
9.140–9.163
Understanding the Principles
Learning the Mechanics
Applying the Concepts—Basic
Applying the Concepts—Intermediate
Applying the Concepts—Advanced
Critical Thinking Challenge
References
Appendix
A:
Summation Notation
Problem
Problem
Problem
Appendix
B:
Tables
Appendix
C:
Calculation Formulas for Analysis of Variance (Independent Sampling)
Short Answers to Selected Odd Exercises
Index
Photo Credits
Chapter
1
Chapter
2
Chapter
3
Chapter
4
Chapter
5
Chapter
6
Chapter
7
Chapter
8
Chapter
9
Chapter
9
Selected Formulas
List of Illustrations
Figure 1.1
Figure 1.2
Figure 1.3
Figure 1. M.1
Figure 1. M.2
Figure 1. M.3
Figure 1. M.4
Figure 1. M.5
Figure 1. M.6
Figure 1. M.7
Figure 1. M.8
Figure 1. M.9
Figure 1. M.10
Figure 1. M.11
Figure 1. M.12
Figure 2.1
Figure 2.2
Figure 2.3
Figure 2.4
Figure 2.5
Figure 2.6
Figure 2.7
Figure SIA2.1
Figure SIA2.2
Figure SIA2.3
SAS output for Exercise 2.15
Figure 2.8
Figure 2.9
Figure 2.10
Figure 2.11
Figure 2.12
Figure 2.13
Figure SIA2.4
Figure 2.14
Figure 2.15
Figure 2.16
Figure 2.17
Figure 2.18a
Figure 2.18b
MINITAB Output for Exercise 2.63
Figure 2.19
Figure 2.20
Figure 2.21
Figure 2.22
Figure 2.23
Figure 2.24
Figure 2.25
Figure SIA2.5
MINITAB Output for Exercise 2.105
Figure 2.26
Figure 2.27
Figure 2.28
Figure 2.29
Figure 2.30
Figure 2.31
Figure 2.32
Figure 2.33
Figure 2.34
Figure SIA2.6
Figure 2.35
Figure 2.36
Figure 2.37
Figure 2.38
Figure 2.39
Figure 2.40
Figure 2.41
MINITAB Output for Exercise 2.173
Numerical Description of Quantitative Data
Figure 2.M.1
Figure 2.M.2
Figure 3.1
Figure 3.2
Figure 3.3
Figure 3.4
Figure 3.5
Figure 3.6
Figure 3.7
Figure 3.8
Figure 3.9
Figure 3.10
Figure 3.11
Figure 3.12
Figure 3.13
Figure 3.14
Figure 3.15
Figure 3.16
Figure 3.17
Figure 3.18
Figure 3.19
Figure 3.20
Figure SIA5.1
Figure 4.1
Figure 4.2
Figure 4.3
Figure 4.4
Figure 4.5
Figure 4.6
Figure 4.7
Histogram for Exercise 4.21
Figure 4.8
Figure 4.9
Figure 4.10
Figure 4.11
Figure 4.12
Figure 4.13
Figure 4.14
Figure 4.15
Figure 4.16
Figure 4.17
Figure 4.18
Figure 4.19
Figure 4.20
Figure 4.21
Figure 4.22
Figure 4.23
Figure 4.24
Figure 4.25
Figure 4.26
Figure 4.27
Figure 4.28
Figure 4.29
Figure SIA4.2
Figure 4.30a
Figure 4.30b
Figure 4.30c
Figure SIA4.3a
Figure SIA4.3b
Figure SIA4.3c
Figure 4.31
Figure 4.32
Figure 4.33
Figure 4.34
Figure 4.35
Figure 4.36
Figure 4.37
Figure 4.38
Figure 4.39
Figure 4.40
Figure 4.41
Figure 4.42
Figure 4.43
Figure 4.44
Figure 4.45
Figure 4.46
Figure 4.M.1
Figure 4.M.2
Figure 4.M.3
Figure 4.M.4
Figure 4.M.5
Figure 4.M.6
Figure 4.M.7
Figure 4.M.8
Figure 4.M.9
Figure 4.M.10
Figure 5.1
Figure 5.2
Figure 5.3
Figure 5.4
Figure 5.5
Figure 5.6
Figure 5.7
Figure 5.8
MINITAB Output for Exercise 5.23
Figure 5.9
Figure 5.10
Figure 5.11
Figure 5.12
Figure 5.13
Figure SIA5.1
Figure 5.14
Figure 5.15
Figure SIA5.2
Figure 5.16
Figure 5.17
Figure 5.18
Figure 5.19
Figure 5.20
Figure 5.21
Figure 5.22
Figure 5.23
Figure 5.24
Figure 5.M.1
Figure 5.M.2
Figure 5.M.3
Figure 5.M.4
Figure 5.M.5
Figure 5.M.6
Figure 5.M.7
Figure 5.M.8
Figure 5.M.9
List of Tables
MINITAB Output for Exercise 2.69
Peripheral refraction differences
Table 2.5 Two Hypothetical Data Sets
Rule 2.1 Using the Mean and Standard Deviation to Describe Data: Chebyshev’s Rule
Rule 2.2 Using the Mean and Standard Deviation to Describe Data: The Empirical Rule
MINITAB Output for Exercise 2.144
Estimates of Daily Collection of Oil
MINITAB Output for Exercise 2.191
MINITAB Output for Exercise 2.201
Table SIA3.1 Wheeling the Seven Numbers 2, 7, 18, 23, 30, 32, and 51
Results for Exercise 3.92
Table 4.1 Probability Distribution for Coin-Toss Experiment: Tabular Form
Table for Exercise 4.34
Table 4.3 Probability Distribution for Physical Fitness Example: Tabular Form
Table 4.7 Describing the 100 EPA Mileage Ratings
Table 4.8 List of Population Parameters and Corresponding Sample Statistics
Data for Exercise 4.209
Table 5.4 Blood Pressure Increases (Points) for Six Patients
Table 5.6 Values of pq for Several Different Values of p
Determining the Target Parameter
Data for Exercise 7.83
Table I Binomial Probabilities
Table II Normal Curve Areas
Table III Critical Values of t
Table IV Critical Values of χ 2
Table V Critical Values of TL and TU for the Wilcoxon Rank Sum Test
Table VI Critical Values of T0 in the Wilcoxon Signed Rank Test
Table VII Percentage Points of the F-Distribution, α=.10
Table VIII Percentage Points of the F-Distribution, α=.05
Table IX Percentage Points of the F-Distribution, α=.025
Table X Percentage Points of the F-Distribution, α=.01
Table XI Critical Values of Spearman’s Rank Correlation Coefficient
Landmarks
Frontmatter
Start of Content
backmatter
List of Illustrations
List of Tables
IFC-1
IFC-2
IFC-3
i
ii
iii
iv
v
vi
vii
viii
ix
x
xi
xii
xiii
xiv
xv
xvi
xvii
xviii
xix
xx
xxi
xxii
xxiii
xxiv
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
IBC-1
IBC-2
IBC-3
IBC-4
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset