Section 2-1:
Sample Spaces and Events
Section 2-2:
Interpretations and Axioms of Probability
Section 2-3:
Addition Rules
Section 2-4:
Conditional Probability
Section 2-5:
Multiplication and Total Probability
Section 2-6:
Independence
Section 2-7:
Baye's Theorem
Section 2-8:
Random Variables
Page 64:
Mind-Expanding Exercises
Chapter 3: Discrete Random Variables and Probability DistributionsSection 3-1:
Discrete Random Variables
Section 3-2:
Probability Distributions and Probability Mass Functions
Section 3-3:
Cumulative Distribution Functions
Section 3-4:
Mean and Variance of a Discrete Random Variable
Section 3-5:
Discrete Uniform Distribution
Section 3-6:
Binomial Distribution
Section 3-7:
Geometric and Negative Binomial Distributions
Section 3-8:
Hypergeometric Distribution
Section 3-9:
Poisson Distribution
Page 103:
Supplemental Exercises
Page 106:
Mind-Expanding Exercises
Chapter 4: Continuous Random Variables and Probability DistributionsSection 4-2:
Probability Distributions and Probability Density Functions
Section 4-3:
Cumulative Distribution Functions
Section 4-4:
Mean and Variance of a Continuous Random Variables
Section 4-5:
Continuous Uniform Distribution
Section 4-6:
Normal Distribution
Section 4-7:
Normal Approximation to the Binomial and Poisson Distributions
Section 4-8:
Exponential Distribution
Section 4-9:
Erlang and Gamma Distributions
Section 4-10:
Weibull Distribution
Section 4-11:
Lognormal Distributions
Section 4-12:
Beta Distribution
Page 151:
Supplemental Exercises
Page 154:
Mind-Expanding Exercises
Chapter 5: Joint Probability DistributionsSection 5-1:
Two or More Random Variables
Section 5-2:
Covariance and Correlation
Section 5-3:
Common Joint Distribution
Section 5-4:
Linear Functions of Random Variables
Section 5-5:
General Functions of Random Variables
Section 5-6:
Moment-Generating Functions
Page 195:
Supplemental Exercises
Page 198:
Mind-Expanding Exercises
Chapter 6: Descriptive StatisticsSection 6-1:
Numerical Summaries of Data
Section 6-2:
Stem-and Leaf Diagrams
Section 6-3:
Frequency Distributions and Histograms
Section 6-4:
Box Plots
Section 6-5:
Time Sequence Plots
Section 6-6:
Scatter Diagrams
Section 6-7:
Probability Plots
Page 233:
Supplemental Exercises
Page 238:
Mind-Expanding Exercises
Chapter 7: Point Estimation of Parameters and Sampling DistributionsSection 7-2:
Sampling Distributions and the Central Limit Theorem
Section 7-3:
General Concepts of Point Estimation
Section 7-4:
Methods of Point Estimation
Page 268:
Supplemental Exercises
Page 269:
Mind-Expanding Exercises
Chapter 8: Statistical Intervals for a Single SampleSection 8-1:
Confidence Interval on the Mean of a Normal Distribution, Variance Known
Section 8-2:
Confidence Interval on the Mean of a Normal Distribution, Variance Unknown
Section 8-3:
Confidence Interval on the Variance and Standard Deviation of a Normal Distribution
Section 8-4:
Large-Sample Confidence Interval for a Population Proportion
Section 8-7:
Tolerance and Prediction Intervals
Page 300:
Supplemental Exercises
Page 303:
Mind-Expanding Exercises
Chapter 9: Test of Hypotheses for a Single SampleSection 9-1:
Hypothesis Testing
Section 9-2:
Tests on the Mean of a Normal Distribution, Variance Known
Section 9-3:
Test on the Mean of a Distribution, Variance Unknown
Section 9-4:
Tests on the Variance and Standard Deviation of a Normal Distribution
Section 9-5:
Tests on a Population Proportion
Section 9-7:
Testing for Goodness of Fit
Section 9-8:
Contigency Table Tests
Section 9-9:
Nonparametric Procedures
Section 9-10:
Equivalence Testing
Section 9-11:
Combining P-Values
Page 368:
Supplemental Exercises
Page 372:
Mind-Expanding Exercises
Chapter 10: Statistical Inference for Two SamplesSection 10-1:
Inference on the Difference in Means of Two Normal Distributions, Variance Known
Section 10-2:
Inference on the Difference in Means of two Normal Distributions, Variances Unknown
Section 10-3:
A Nonparametric Test for the Difference in Two Means
Section 10-4:
Paired t-Test
Section 10-5:
Inference on the Variance of Two Normal Distributions
Section 10-6:
Inference on Two Population Proportions
Page 421:
Supplemental Exercises
Page 425:
Mind-Expanding Exercises
Chapter 11: Simple Linear Regression and CorrelationSection 11-2:
Simple Linear Regression
Section 11-4:
Hypothesis Tests in Simple Linear Regression
Section 11-5:
Confidence Intervals
Section 11-7:
Adequacy of the Regression Model
Section 11-8:
Correlation
Section 11-9:
Regression on Transformed Variables
Section 11-10:
Logistic Regression
Page 472:
Supplemental Exercises
Page 475:
Mind-Expanding Exercises
Chapter 12: Multiple Linear RegressionSection 12-1:
Multiple Linear Regression Model
Section 12-2:
Hypothesis Tests in Multiple Linear Regression
Section 12-3:
Confidence Intervals in Multiple Linear Regression
Section 12-5:
Model Adequacy Checking
Section 12-6:
Aspects of Multiple Regression Modeling
Page 533:
Supplemental Exercises
Page 539:
Mind-Expanding Exercises
Chapter 13: Design and Analysis of Single-Factor Experiments: The Analysis of VarianceSection 13-2:
Completely Randomized Single-Factor Experiment
Section 13-3:
The Random-Effects Model
Section 13-4:
Randomized Complete Block Design
Page 571:
Supplemental Exercises
Page 573:
Mind-Expanding Exercises
Chapter 14: Design of Experiments with Several FactorsSection 14-3:
Two-Factor Factorial Experiments
Section 14-5:
Factorial Designs
Section 14-6:
Blocking and Confounding in 2k Design
Section 14-7:
Fractional Replication of the 2k Design
Section 14-8:
Response Surface Methods and Designs
Page 653:
Supplemental Exercises
Page 662:
Mind-Expanding Exercises
Page 589:
Exercises
Page 593:
Exercises
Chapter 15: Statistical Quality ControlSection 15-3:
X and R or S Control Charts
Section 15-4:
Control Charts for Individual Measurements
Section 15-5:
Process Capability
Section 15-6:
Attribute Control Charts
Section 15-7:
Control Chart Performance
Section 15-8:
Time-Weighted Charts
Section 15-9:
Other SPC Problem-Solving Tools
Page 723:
Supplemental Exercises
Page 733:
Mind-Expanding Exercises
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