A First Course in Statistics

Chapter 1 Statistics, Data, and Statistical Thinking 1.1 The Science of Statistics

1.2 Types of Statistical Applications

1.3 Fundamental Elements of Statistics

1.4 Types of Data

1.5 Collecting Data

1.6 The Role of Statistics in Critical Thinking

Statistics in Action: USA Weekend Teen Surveys - Are Boys Really from Mars and Girls from Venus?

Using Technology: Creating and Listing Data in MINITAB



Chapter 2 Methods for Describing Sets of Data

2.1 Describing Qualitative Data

2.2 Graphical Methods for Describing Quantitative Data

2.3 Summation Notation

2.4 Numerical Measures of Central Tendency

2.5 Numerical Measures of Variability

2.6 Interpreting the Standard Deviation

2.7 Numerical Measures of Relative Standing

2.8 Methods for Detecting Outliers (Optional)

2.9 Graphing Bivariate Relationships (Optional)

2.10 Distorting the Truth with Descriptive Techniques

Statistics In Action: The "Eye Cue" Test: Does Experience Improve Performance?

Using Technology: Describing Data in MINITAB



Chapter 3 Probability

3.1 Events, Sample Spaces, and Probability

3.2 Unions and Intersections

3.3 Complementary Events

3.4 The Additive Rule and Mutually Exclusive Events

3.5 Conditional Probability

3.6 The Multiplicative Rule and Independent Events

3.7 Random Sampling

Statistics In Action: Lotto Buster!

Using Technology: Generating a Random Sample in MINITAB



Chapter 4 Random Variables and Probability Distributions

4.1 Two Types of Random Variables

4.2 Probability Distributions for Discrete Random Variables

4.3 The Binomial Random Distribution

4.4 Probability Distributions for Continuous Random Variables

4.5 The Normal Distribution

4.6 Descriptive Methods for Assessing Normality

4.7 Approximating a Binomial Distribution with a Normal Distribution (Optional)

4.8 Sampling Distributions

4.9 The Central Limit Theorem

Statistics in Action: Super Weapons Development - Optimizing the Hit Ratio

Using Technology: Binomial Probabilities, Normal Probabilities, and Normal Probability Plots in MINITAB



Chapter 5 Inferences Based on a Single Sample: Estimation with Confidence Intervals

5.1 Large-Sample Confidence Interval for a Population Mean

5.2 Small-Sample Confidence Interval for a Population Mean

5.3 Large-Sample Confidence Interval for a Population Proportion

5.4 Determining the Sample Size

5.5 Identifying the Parameter to be Estimated

Statistics in Action:Speed - Improving the Sprint Times of High School Football Players

Using Technology: Confidence Intervals in MINITAB



Chapter 6 Inferences Based on a Single Sample: Tests of Hypothesis

6.1 The Elements of a Test of Hypothesis

6.2 Large-Sample Test of Hypothesis About a Population Mean

6.3 Observed Significance Levels: p-Values

6.4 Small-Sample Test of Hypothesis About a Population Mean

6.5 Large-Sample Test of Hypothesis About a Population Proportion

6.6 A Nonparametric Test about a Population Median (Optional)

Statistics in Action: Diary of a Kleenex User

Using Technology: Tests of Hypothesis in MINITAB



Chapter 7 Comparing Population Means

7.1 Comparing Two Population Means: Independent Sampling

7.2 Comparing Two Population Means: Paired Difference Experiments

7.3 Determining the Sample Size

7.4 A Nonparametric Test for Comparing Two Population: Independent Sampling (Optional)

7.5 A Nonparametric Test for Comparing Two Populations: Paired Difference Experiments (Optional)

7.6 Comparing Three or More Population Means: Analysis of Variance (Optional)

Statistics in Action: On the Trail of the Cockroach

Using Technology: Comparing Means in MINITAB



Chapter 8 Comparing Population Proportions

8.1 Comparing Two Population Proportions: Independent Sampling

8.2 Determining the Sample Size

8.3 Testing Categorical Probabilities: Multinomial Experiment

8.4 Testing Categorical Probabilities: Two-Way (Contingency) Table

Statistics in Action: A Study of Coupon Users--Mail Versus the Internet

Using Technology: Categorical Data Analyses Using MINITAB



Chapter 9 Simple Linear Regression

9.1 Probabilistic Models

9.2 Fitting the Model: The Least Squares Approach

9.3 Model Assumptions

9.4 An Estimator of ?2

9.5 Assessing the Utility of the Model: Making Inferences About the Slope ?1

9.6 The Coefficient of Correlation

9.7 The Coefficient of Determination

9.8 Using the Model for Estimation and Prediction

9.9 A Complete Example

9.10 A Nonparametric Test for Correlation (Optional)

Statistics in Action: Can "Dowsers" Really Detect Water?

Using Technology: Simple Linear Regression in MINITAB



Appendix A: Tables

Table I Random Numbers

Table II Binomial Probabilities

Table III Normal Curve Areas

Table IV Critical Values of t

Table V Critical Values of TL and TU for the Wilcoxon Rank Sum Test: Independent Samples

Table VI Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test

Table VII Percentage Points of the F Distribution, ?=.10

Table VIII Percentage Points of the F Distribution, ?=.05

Table IX Percentage Points of the F Distribution, ?=.025

Table X Percentage Points of the F Distribution, ?=.01

Table XI Critical Values of ?2

Table XII Critical Values of Spearman's Rank Correlation Coefficient



Appendix B: Calculation Formulas for Analysis of Variance (Independent Sampling)



Short Answers to Selected Odd-Numbered Exercises



Index