Essentials of business statistics

Chapter 1. An Introduction to Business Statistics
	1.1. Data
	1.2. Data Sources
	1.3. Populations and Samples
	1.4. Three Case Studies That Illustrate Sampling and Statistical Inference
	1.5. Ratio, Interval, Ordinal, and Nominative Scales of Measurement (Optional)
	Appendix 1.1. Getting Started with Excel
	Appendix 1.2. Getting Started with MegaStat
	Appendix 1.3. Getting Started with MINITAB
Chapter 2. Descriptive Statistics: Tabular and Graphical Methods
	2.1. Graphically Summarizing Qualitative Data
	2.2. Graphically Summarizing Quantitative Data
	2.3. Dot Plots
	2.4. Stem-and-Leaf Displays
	2.5. Contingency Tables (Optional)
	2.6. Scatter Plots (Optional)
	2.7. Misleading Graphs and Charts (Optional)
	Appendix 2.1. Tabular and Graphical Methods Using Excel
	Appendix 2.2. Tabular and Graphical Methods Using MegaStat
	Appendix 2.3. Tabular and Graphical Methods Using MINITAB
Chapter 3. Descriptive Statistics: Numerical Methods
	3.1. Describing Central Tendency
	3.2. Measures of Variation
	3.3. Percentiles, Quartiles, and Box-and-Whiskers Displays
	3.4. Covariance, Correlation, and the Least Squares Line (Optional)
	3.5. Weighted Means and Grouped Data (Optional)
	3.6. The Geometric Mean (Optional)
	Appendix 3.1. Numerical Descriptive Statistics Using Excel
	Appendix 3.2. Numerical Descriptive Statistics Using MegaStat
	Appendix 3.3. Numerical Descriptive Statistics Using MINITAB
Chapter 4. Probability
	4.1. Probability and Sample Spaces
	4.2. Probability and Events
	4.3. Some Elementary Probability Rules
	4.4. Conditional Probability and Independence
	4.5. Bayes’ Theorem (Optional)
	4.6. Counting Rules (Optional)
Chapter 5. Discrete Random Variables
	5.1. Two Types of Random Variables
	5.2. Discrete Probability Distributions
	5.3. The Binomial Distribution
	5.4. The Poisson Distribution (Optional)
	5.5. The Hypergeometric Distribution (Optional)
	5.6. Joint Distributions and the Covariance (Optional)
	Appendix 5.1. Binomial, Poisson, and Hypergeometric Probabilities Using Excel
	Appendix 5.2. Binomial, Poisson, and Hypergeometric Probabilities Using MegaStat
	Appendix 5.3. Binomial, Poisson, and Hypergeometric Probabilities Using MINITAB
Chapter 6. Continuous Random Variables
	6.1. Continuous Probability Distributions
	6.2. The Uniform Distribution
	6.3. The Normal Probability Distribution
	6.4. Approximating the Binomial Distribution by Using the Normal Distribution (Optional)
	6.5. The Exponential Distribution (Optional)
	6.6. The Normal Probability Plot (Optional)
	Appendix 6.1. Normal Distribution Using Excel
	Appendix 6.2. Normal Distribution Using MegaStat
	Appendix 6.3. Normal Distribution Using  MINITAB
Chapter 7. Sampling and Sampling Distributions
	7.1. Random Sampling
	7.2. The Sampling Distribution of the Sample Mean
	7.3. The Sampling Distribution of the Sample Proportion
	7.4. Stratified Random, Cluster, and Systematic Sampling (Optional)
	7.5. More about Surveys and Errors in Survey Sampling (Optional)
	7.6. Derivation of the Mean and the Variance of the Sample Mean (Optional)
	Appendix 7.1. Generating Random Numbers Using Excel
	Appendix 7.2. Generating Random Numbers Using MegaStat
	Appendix 7.3. Generating Random Numbers Using MINITAB
Chapter 8. Confidence Intervals
	8.1. z-Based Confidence Intervals for a Population Mean: σ Known
	8.2. t-Based Confidence Intervals for a Population Mean: σ Unknown
	8.3. Sample Size Determination
	8.4. Confidence Intervals for a Population Proportion
	8.5. Confidence Intervals for Parameters of Finite Populations (Optional)
	Appendix 8.1. Confidence Intervals Using Excel
	Appendix 8.2. Confidence Intervals Using MegaStat
	Appendix 8.3. Confidence Intervals Using MINITAB
Chapter 9. Hypothesis Testing
	9.1. The Null and Alternative Hypotheses and Errors in Hypothesis Testing
	9.2. z Tests about a Population Mean: σ Known
	9.3. t Tests about a Population Mean: σ Unknown
	9.4. z Tests about a Population Proportion
	9.5. Type II Error Probabilities and Sample Size Determination (Optional)
	9.6. The Chi-Square Distribution
	9.7. Statistical Inference for a Population Variance (Optional)
	Appendix 9.1. One-Sample Hypothesis Testing Using Excel
	Appendix 9.2. One-Sample Hypothesis Testing Using MegaStat
	Appendix 9.3. One-Sample Hypothesis Testing Using MINITAB
Chapter 10. Statistical Inferences Based on Two Samples
	10.1. Comparing Two Population Means by Using Independent Samples
	10.2. Paired Difference Experiments
	10.3. Comparing Two Population Proportions by Using Large, Independent Samples
	10.4. The F Distribution
	10.5. Comparing Two Population Variances by Using Independent Samples
	Appendix 10.1. Two-Sample Hypothesis Testing Using Excel
	Appendix 10.2. Two-Sample Hypothesis Testing Using MegaStat
	Appendix 10.3. Two-Sample Hypothesis Testing Using MINITAB
Chapter 11. Experimental Design and Analysis of Variance
	11.1. Basic Concepts of Experimental Design
	11.2. One-Way Analysis of Variance
	11.3. The Randomized Block Design
	11.4. Two-Way Analysis of Variance
	Appendix 11.1. Experimental Design and Analysis of Variance Using Excel
	Appendix 11.2. Experimental Design and Analysis of Variance Using MegaStat
	Appendix 11.3. Experimental Design and Analysis of Variance Using MINITAB
Chapter 12. Chi-Square Tests
	12.1. Chi-Square Goodness-of-Fit Tests
	12.2. A Chi-Square Test for Independence
	Appendix 12.1. Chi-Square Tests Using Excel
	Appendix 12.2. Chi-Square Tests Using MegaStat
	Appendix 12.3. Chi-Square Tests Using MINITAB
Chapter 13. Simple Linear Regression Analysis
	13.1. The Simple Linear Regression Model and the Least Squares Point Estimates
	13.2. Model Assumptions and the Standard Error
	13.3. Testing the Significance of the Slope and y-Intercept
	13.4. Confidence and Prediction Intervals
	13.5. Simple Coefficients of Determination and Correlation
	13.6. Testing the Significance of the Population Correlation Coefficient (Optional)
	13.7. An F-Test for the Model
	13.8. Residual Analysis
	Appendix 13.1. Simple Linear Regression Analysis Using Excel
	Appendix 13.2. Simple Linear Regression Analysis Using MegaStat
	Appendix 13.3. Simple Linear Regression Analysis Using MINITAB
Chapter 14. Multiple Regression and Model Building
	14.1. The Multiple Regression Model and the Least Squares Point Estimates
	14.2. Model Assumptions and the Standard Error
	14.3. R² and Adjusted R²
	14.4. The Overall F-Test
	14.5. Testing the Significance of an Independent Variable
	14.6. Confidence and Prediction Intervals
	14.7. The Sales Representative Case: Evaluating Employee Performance
	14.8. Using Dummy Variables to Model Qualitative Independent Variables
	14.9. Using Squared and Interaction Variables
	14.10. Model Building and the Effects of Multicollinearity
	14.11. Residual Analysis in Multiple Regression
	14.12. Logistic Regression
	Appendix 14.1. Multiple Regression Analysis Using Excel
	Appendix 14.2. Multiple Regression Analysis Using MegaStat
	Appendix 14.3. Multiple Regression Analysis Using MINITAB
Appendix A. Statistical Tables
Answers to Most Odd-Numbered Exercises
References
Photo Credits
Subject Index