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| Statistics, Data, and Statistical Thinking | |
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| The Science of Statistics | |
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| Types of Statistical Applications in Business | |
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| Fundamental Elements of Statistics | |
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| Processes (Optional) | |
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| Types of Data | |
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| Collecting Data: Sampling and Related Issues | |
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| Critical Thinking with Statistics | |
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| Statistics in Action: A 20/20 View of Surveys: Fact or Fiction? | |
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| Keep the Change: Collecting Data | |
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| Identifying Misleading Statistics | |
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| Using Technology: Accessing and Listing Data; Random Sampling | |
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| Methods for Describing Sets of Data | |
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| Describing Qualitative Data | |
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| Graphical Methods for Describing Quantitative Data | |
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| Numerical Measures of Central Tendency | |
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| Numerical Measures of Variability | |
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| Using the Mean and Standard Deviation to Describe Data | |
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| Numerical Measures of Relative Standing | |
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| Methods for Detecting Outliers: Box Plots and z-Scores | |
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| Graphing Bivariate Relationships (Optional) | |
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| The Time Series Plot (Optional) | |
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| Distorting the Truth with Descriptive Techniques | |
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| Statistics in Action: Can Money Buy Love? | |
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| Real Estate Sales | |
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| Keep the Change: Measures of Central Tendency and Variability | |
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| Using Technology: Describing Data | |
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| Making Business Decisions: The Kentucky Milk Case Part 1 (Covers Chapters 1 and 2) | |
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| Probability | |
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| Events, Sample Spaces, and Probability | |
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| Unions and Intersections | |
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| Complementary Events | |
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| The Additive Rule and Mutually Exclusive Events | |
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| Conditional Probability | |
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| The Multiplicative Rule and Independent Events | |
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| Bayes's Rule | |
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| Statistics in Action: Lotto Buster! | |
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| Exit Polls: Conditional Probability | |
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| Keep the Change: Independent Events | |
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| Using Technology: Combinations and Permutations | |
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| Random Variables and Probability Distributions | |
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| Two Types of Random Variables | |
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| Discrete Random Variables | |
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| Probability Distributions for Discrete Random Variables | |
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| The Binomial Distribution | |
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| Other Discrete Distributions: Poisson and Hypergeometric | |
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| Continuous Random Variables | |
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| Probability Distributions for Continuous Random Variables | |
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| The Normal Distribution | |
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| Descriptive Methods for Assessing Normality | |
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| Other Continuous Distributions: Uniform and Exponential | |
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| Statistics in Action: Probability in a Reverse Cocaine Sting: Was Cocaine Really Sold? | |
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| Warehouse Club Memberships: Exploring a Binomial Random Variable | |
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| Identifying the Type of Probability Distribution | |
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| Using Technology: Discrete Probabilities, Continuous Probabilities, and Normal Probability Plots | |
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| Sampling Distributions | |
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| The Concept of a Sampling Distribution | |
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| Properties of Sampling Distributions: Unbiasedness and Minimum Variance | |
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| The Sampling Distribution of the Sample Mean and the Central Limit Theorem | |
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| The Sampling Distribution of the Sample Proportion | |
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| Statistics in Action: The Insomnia Pill: Is It Effective? | |
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| Simulating a Sampling Distribution Cell Phone Usage | |
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| Using Technology: Simulating a Sampling Distribution | |
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| Making Business Decisions: The Furniture Fire Case (Covers Chapters 3-5) | |
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| Inferences Based on a Single Sample: Estimation with Confidence Intervals | |
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| Identifying and Estimating the Target Parameter | |
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| Confidence Interval for a Population Mean: Normal (z) Statistic | |
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| Confidence Interval for a Population Mean: Student's t-Statistic | |
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| Large-Sample Confidence Interval for a Population Proportion | |
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| Determining the Sample Size | |
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| Finite Population Correction for Simple Random Sampling (Optional) | |
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| Confidence Interval for a Population Variance (Optional) | |
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| Inferences Based on a Single Sample: Estimation with Confidence Intervals | |
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| Statistics in Action: Medicare Fraud Investigations | |
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| Conducting a Pilot Study | |
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| Using Technology: Confidence Intervals | |
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| Inferences Based on a Single Sample: Tests of Hypotheses | |
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| The Elements of a Test of Hypothesis | |
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| Formulating Hypotheses and Setting Up the Rejection Region | |
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| Observed Significance Levels: p-Values | |
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| Test of Hypothesis about a Population Mean: Normal (z) Statistic | |
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| Test of Hypothesis about a Population Mean: Student's t-Statistic | |
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| Large-Sample Test of Hypothesis about a Population Proportion | |
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| Test of Hypothesis about a Population Variance | |
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| Calculating Type II Error Probabilities: More about b (Optional) | |
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| Statistics in Action: Diary of a Kleenex� User-How Many Tissues in a Box? | |
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| Challenging a Company's Claim: Tests of Hypotheses | |
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| Keep the Change: Tests of Hypotheses | |
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| Using Technology: Tests of Hypotheses | |
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| Inferences Based on Two Samples: Confidence Intervals and Tests of Hypotheses | |
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| Identifying the Target Parameter | |
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| Comparing Two Population Means: Independent Sampling | |
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| Comparing Two Population Means: Paired Difference Experiments | |
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| Comparing Two Population Proportions: Independent Sampling | |
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| Determining the Required Sample Size | |
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| Comparing Two Population Variances: Independent Sampling | |
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| Statistics in Action: ZixIt Corp. v. Visa USA Inc.-A Libel Case | |
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| Box Office Receipts: Comparing Population Means | |
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| Keep the Change: Inferences Based on Two Samples | |
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| Using Technology: Two-Sample Inferences | |
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| Making Business Decisions: The Kentucky Milk Case-Part II (Covers Chapters 6-8) | |
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| Design of Experiments and Analysis of Variance | |
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| Elements of a Designed Experiment | |
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| The Completely Randomized Design: Single Factor | |
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| Multiple Comparisons of Means | |
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| The Randomized Block Design | |
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| Factorial Experiments: Two Factors | |
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| Statistics in Action: Pollutants at a Housing Development-A Case of Mishandling Small Samples | |
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| Designed vs. Observational Experiments | |
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| Using Technology: Analysis of Variance | |
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| Categorical Data Analysis | |
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| Categorical Data and the Multinomial Experiment | |
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| Testing Category Probabilities: One-Way Table | |
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| Testing Category Probabilities: Two-Way (Contingency) Table | |
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| A Word of Caution about Chi-Square Tests | |
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| Statistics in Action: The Case of the Ghoulish Transplant Tissue-Who Is Responsible for Paying Damages? | |
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| Binomial vs. Multinomial Experiments | |
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| Contingency Tables | |
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| Using Technology: Chi-Square Analyses | |
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| Making Business Decisions: Discrimination in the Workplace (Covers Chapters 9 and 10) | |
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| Simple Linear Regression | |
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| Probabilistic Models | |
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| Fitting the Model: The Least Squares Approach | |
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| Model Assumptions | |
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| Assessing the Utility of the Model: Making Inferences about the Slope b <Sub>1</Sub> | |
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| The Coefficients of Correlation and Determination | |
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| Using the Model for Estimation and Prediction | |
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| A Complete Example | |
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| Statistics in Action: Legal Advertising-Does It Pay? | |
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| Apply Simple Linear Regression to Your Favorite Data | |
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| Using Technology: Simple Linear Regression | |
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| Multiple Regression and Model Building | |
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| Multiple Regression Models | |
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| First-Order Models with Quantitative Independent Variables | |
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| Estimating and Making Inferences about the b Parameters | |
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| Evaluating Overall Model Utility | |
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| Using the Model for Estimation and Prediction | |
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| Model Building in Multiple Regression | |
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| Interaction Models | |
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| Quadratic and Other Higher-Order Models | |
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| Qualitative (Dummy) Variable Models | |
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| Models with Both Quantitative and Qualitative Variables | |
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| Comparing Nested Models | |
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| Stepwise Regression | |
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| Multiple Regression Diagnostics | |
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| Residual Analysis: Checking the Regression Assumptions | |
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| Some Pitfalls: Estimability, Multicollinearity, and Extrapolation | |
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| Statistics in Action: Bid Rigging in the Highway Construction Industry | |
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| Insurance Premiums: Collecting Data for Several Variables | |
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| Collecting Data and Fitting a Multiple Regression Model | |
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| Using Technology: Multiple Regression | |
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| Making Business Decisions: The Condo Sales Case (Covers Chapters 11 and 12) | |
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| Methods for Quality Improvement: Statistical Process Control (Available on CD) | |
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| Quality, Processes, and Systems | |
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| Statistical Control | |
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| The Logic of Control Charts | |
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| A Control Chart for Monitoring the Mean of a Process: The [x-bar]-Chart | |
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| A Control Chart for Monitoring the Variation of a Process: The R-Chart | |
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| A Control Chart for Monitoring the Proportion of Defectives Generated by a Process: The p-Chart | |
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| Diagnosing the Causes of Variation | |
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| Capability Analysis | |
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| Statistics in Action: Testing Jet Fuel Additive for Safety | |
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| Quality Control: Consistency | |
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| Using Technology: Control Charts | |
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| MAKING BUSINESS DECISIONS: The Gasket Manufacturing Case (Covers Chapter 13) | |
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| Time Series: Descriptive Analyses, Models, and Forecasting (Available on CD) | |
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| Descriptive Analysis: Index Numbers | |
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| Descriptive Analysis: Exponential Smoothing | |
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| Time Series Components | |
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| Forecasting: Exponential Smoothing | |
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| Forecasting Trends: Holt's Method | |
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| Measuring Forecast Accuracy: MAD and RMSE | |
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| Forecasting Trends: Simple Linear Regression | |
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| Seasonal Regression Models | |
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| Autocorrelation and the Durbin-Watson Test | |
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| Statistics in Action: Forecasting the Monthly Sales of a New Cold Medicine | |
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| Time Series | |
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| Using Technology: Forecasting | |
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| Nonparametric Statistics (Available on CD) | |
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| Introduction: Distribution-Free Tests | |
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| Single Population Inferences | |
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| Comparing Two Populations: Independent Samples | |
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| Comparing Two Populations: Paired Difference Experiment | |
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| Comparing Three or More Populations: Completely Randomized Design | |
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| Comparing Three or More Populations: Randomized Block Design | |
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| Rank Correlation | |
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| Statistics in Action: How Vulnerable Are New Hampshire Wells to Groundwater Contamination? | |
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| Keep the Change: Nonparametric Statistics | |
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| Using Technology: Nonparametric Tests | |
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| Making Business Decisions: Detecting "Sales Chasing" (Covers Chapters 10 and 15) | |
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| Summation Notation | |
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| Basic Counting Rules | |
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| Calculation Formulas for Analysis of Variance | |
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| Formulas for the Calculations in the Completely Randomized Design | |
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| Formulas for the Calculations in the Randomized Block Design | |
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| Formulas for the Calculations for a Two-Factor Factorial Experiment | |
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| Tukey's Multiple Comparisons Procedure (Equal Sample Sizes) | |
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| Bonferroni Multiple Comparisons Procedure (Pairwise Comparisons) | |
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| Scheff�'s Multiple Comparisons Procedure (Pairwise Comparisons) | |
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| Tables | |
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| Binomial Probabilities | |
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| Normal Curve Areas | |
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| Critical Values of t | |
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| Critical Values of x <Sup>2</Sup> | |
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| Percentage Points of the F-Distribution, � = .10 | |
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| Percentage Points of the F-Distribution, � = .05 | |
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| Percentage Points of the F-Distribution, � = .025 | |
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| Percentage Points of the F-Distribution, � = .01 | |
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| Control Chart Constants | |
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| Critical Values for the Durbin-Watson d-Statistic, � = .05 | |
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| Critical Values for the Durbin-Watson d-Statistic, � = .01 | |
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| Critical Values of T<Sub>L</Sub> and T<Sub>u</Sub> for the Wilcoxon Rank Sum Test: Independent Samples | |
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| Critical Values of T0 in the Wilcoxon Paired Difference Signed Rank Test | |
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| Critical Values of Spearman's Rank Correlation Coefficient | |
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| Critical Values of the Studentized Range, � = .05 | |
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| Answers to Selected Exercises | |
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| Index Credits | |