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: Sampling and Related Issues
1.6 The Role of Statistics in Critical Thinking and Ethics
Statistics in Action: Social Media Network Usage—Are You Linked In?
Using Technology: MINITAB: Accessing and Listing Data
2. Methods for Describing Sets of Data
2.1 Describing Qualitative Data
2.2 Graphical Methods for Describing Quantitative Data
2.3 Numerical Measures of Central Tendency
2.4 Numerical Measures of Variability
2.5 Using the Mean and Standard Deviation to Describe Data
2.6 Numerical Measures of Relative Standing
2.7 Methods for Detecting Outliers: Box Plots and z-Scores
2.8 Graphing Bivariate Relationships (Optional)
2.9 Distorting the Truth with Descriptive Statistics
Statistics in Action: Body Image Dissatisfaction: Real or Imagined?
Using Technology: MINITAB: Describing Data
TI-83/TI–84 Plus Graphing Calculator: Describing Data
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 Some Additional Counting Rules (Optional)
3.8 Bayes’s Rule (Optional)
Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?
Using Technology: TI-83/TI-84 Plus Graphing Calculator: Combinations and Permutations
4. Discrete Random Variables
4.1 Two Types of Random Variables
4.2 Probability Distributions for Discrete Random Variables
4.3 Expected Values of Discrete Random Variables
4.4 The Binomial Random Variable
4.5 The Poisson Random Variable (Optional)
4.6 The Hypergeometric Random Variable (Optional)
Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold?
Using Technology: MINITAB: Discrete Probabilities
TI-83/TI-84 Plus Graphing Calculator: Discrete Random Variables and Probabilities
5. Continuous Random Variables
5.1 Continuous Probability Distributions
5.2 The Uniform Distribution
5.3 The Normal Distribution
5.4 Descriptive Methods for Assessing Normality
5.5 Approximating a Binomial Distribution with a Normal Distribution (Optional)
5.6 The Exponential Distribution (Optional)
Statistics in Action: Super Weapons Development—Is the Hit Ratio Optimized?
Using Technology: MINITAB: Continuous Random Variable Probabilities and Normal Probability Plots
TI-83/TI-84 Plus Graphing Calculator: Normal Random Variable and Normal Probability Plots
6. Sampling Distributions
6.1 The Concept of a Sampling Distribution
6.2 Properties of Sampling Distributions: Unbiasedness and Minimum Variance
6.3 The Sampling Distribution of (x-bar) and the Central Limit Theorem
6.4 The Sampling Distribution of the Sample Proportion
Statistics in Action: The Insomnia Pill: Is It Effective?
Using Technology: MINITAB: Simulating a Sampling Distribution
7. Inferences Based on a Single Sample: Estimation with Confidence Intervals
7.1 Identifying and Estimating the Target Parameter
7.2 Confidence Interval for a Population Mean: Normal (z) Statistic
7.3 Confidence Interval for a Population Mean: Student’s t-Statistic
7.4 Large-Sample Confidence Interval for a Population Propo
