First Course in Statistics, A, Global Edition

<p>1. Statistics, Data, and Statistical Thinking</p> <p>1.1 The Science of Statistics</p> <p>1.2 Types of Statistical Applications</p> <p>1.3 Fundamental Elements of Statistics</p> <p>1.4 Types of Data</p> <p>1.5 Collecting Data: Sampling and Related Issues</p> <p>1.6 The Role of Statistics in Critical Thinking and Ethics</p> <p>Statistics in Action: Social Media Network Usage—Are You Linked In?</p> <p>Using Technology: MINITAB: Accessing and Listing Data</p> <p>2. Methods for Describing Sets of Data</p> <p>2.1 Describing Qualitative Data</p> <p>2.2 Graphical Methods for Describing Quantitative Data</p> <p>2.3 Numerical Measures of Central Tendency</p> <p>2.4 Numerical Measures of Variability</p> <p>2.5 Using the Mean and Standard Deviation to Describe Data</p> <p>2.6 Numerical Measures of Relative Standing</p> <p>2.7 Methods for Detecting Outliers: Box Plots and z-Scores</p> <p>2.8 Graphing Bivariate Relationships (Optional)</p> <p>2.9 Distorting the Truth with Descriptive Statistics</p> <p>Statistics in Action: Body Image Dissatisfaction: Real or Imagined?</p> <p>Using Technology: MINITAB: Describing Data</p> <p>TI-83/TI–84 Plus Graphing Calculator: Describing Data</p> <p>3. Probability</p> <p>3.1 Events, Sample Spaces, and Probability</p> <p>3.2 Unions and Intersections</p> <p>3.3 Complementary Events</p> <p>3.4 The Additive Rule and Mutually Exclusive Events</p> <p>3.5 Conditional Probability</p> <p>3.6 The Multiplicative Rule and Independent Events</p> <p>Statistics in Action: Lotto Buster! Can You Improve Your Chance of Winning?</p> <p>Using Technology: TI-83/TI-84 Plus Graphing Calculator: Combinations and Permutations</p> <p>4. Random Variables and Probability Distributions</p> <p>4.1 Two Types of Random Variables</p> <p>4.2 Probability Distributions for Discrete Random Variables</p> <p>4.3 The Binomial Random Variable</p> <p>4.4 Probability Distributions for Continuous Random Variables</p> <p>4.5 The Normal Distribution</p> <p>4.6 Descriptive Methods for Assessing Normality</p> <p>4.7 Approximating a Binomial Distribution with a Normal Distribution (Optional)</p> <p>4.8 Sampling Distributions</p> <p>4.9 The Sampling Distribution of x̅ and the Central Limit Theorem</p> <p>Statistics in Action: Super Weapons Development – Is the Hit Ratio Optimized?</p> <p>Using Technology: MINITAB: Discrete Probabilities</p> <p>&nbsp;</p> <p>5. Inferences Based on a Single Sample</p> <p>5.1 Identifying and Estimating the Target Parameter</p> <p>5.2 Confidence Interval for a Population Mean: Normal (z) Statistic</p> <p>5.3 Confidence Interval for a Population Mean: Student’s t-Statistic</p> <p>5.4 Large-Sample Confidence Interval for a Population Proportion</p> <p>5.5 Determining the Sample Size</p> <p>5.6 Confidence Interval for a Population Variance (Optional)</p> <p>Statistics in Action: Medicare Fraud Investigations</p> <p>Using Technology: MINITAB: Confidence Intervals</p> <p>6. Inferences Based on a Single Sample</p> <p>6.1 The Elements of a Test of Hypothesis</p> <p>6.2 Formulating Hypotheses and Setting Up the Rejection Region</p> <p>6.3 Observed Significance Levels: p-values</p> <p>6.4 Test of Hypothesis about a Population Mean: Normal (z) Statistic</p> <p>6.5 Test of Hypothesis about a Population Mean: Student’s t-Statistic</p> <p>6.6 Large-Sample Test of Hypothesis about a Population Proportion</p> <p>6.7 Test of Hypothesis about a Population Variance (Optional)</p> <p>6.8 A Nonparametric Test about a Population Median (Optional)</p> <p>Statistics in Action: Diary of a KLEENEX User How Many Tissues in a Box?</p> <p>Using Technology: MINITAB: Tests of Hypotheses</p> <p>TI-83/TI-84 Plus Graphing Calculator: Tests of Hypotheses</p> <p>7. Comparing Population Means</p> <p>7.1 Identifying the Target Parameter</p> <p>7.2 Comparing Two Population Means: Independent Sampling</p> <p>7.3 Comparing Two Population Means: Paired Difference Experiments</p> <p>7.4 Determining the Samp</p>