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ISBN-13 : 9798214350462
Author: David Anderson
Get more out of your statistics course than simply solving equations. Discover how statistical information enables strong decisions in today’s business world with STATISTICS FOR BUSINESS AND ECONOMICS, REVISED 13E. Sound methodology combines with a proven problem-scenario approach, and meaningful applications for the most powerful approach to mastering critical business statistics. This edition’s prestigious author team brings together more than 25 years of unmatched experience to this thoroughly updated text. More than 350 real business examples, timely cases, and memorable exercises present the latest statistical data and business information with unwavering accuracy. To ensure the most relevant coverage, this edition includes coverage of popular commercial statistical software Minitab 17 and Excel 2016.
Statistics for Business and Economics 13th Table of contents:
Chapter 1. Data and Statistics
1.1. Applications in Business and Economics
Accounting
Finance
Marketing
Production
Economics
Information Systems
1.2. Data
Elements, Variables, and Observations
Scales of Measurement
Categorical and Quantitative Data
Cross-Sectional and Time Series Data
1.3. Data Sources
Existing Sources
Observational Study
Experiment
Time and Cost Issues
Data Acquisition Errors
1.4. Descriptive Statistics
1.5. Statistical Inference
1.6. Analytics
1.7. Big Data and Data Mining
1.8. Computers and Statistical Analysis
1.9. Ethical Guidelines for Statistical Practice
Summary
Glossary
Supplementary Exercises
Chapter 2. Descriptive Statistics: Tabular and Graphical Displays
2.1. Summarizing Data for a Categorical Variable
Frequency Distribution
Relative Frequency and Percent Frequency Distributions
Bar Charts and Pie Charts
Exercises: Methods
Exercises: Applications
2.2. Summarizing Data for a Quantitative Variable
Frequency Distribution
Relative Frequency and Percent Frequency Distributions
Dot Plot
Histogram
Cumulative Distributions
Stem-and-Leaf Display
Exercises: Methods
Exercises: Applications
2.3. Summarizing Data for Two Variables Using Tables
Crosstabulation
Simpson’s Paradox
Exercises: Methods
Exercises: Applications
2.4. Summarizing Data for Two Variables Using Graphical Displays
Scatter Diagram and Trendline
Side-by-Side and Stacked bar Charts
Exercises: Methods
Exercises: Applications
2.5. Data Visualization: Best Practices in Creating Effective Graphical Displays
Creating Effective Graphical Displays
Choosing the Type of Graphical Display
Data Dashboards
Data Visualization in Practice: Cincinnati Zoo and Botanical Garden
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem 1. Pelican Stores
Case Problem 2. Motion Picture Industry
Case Problem 3. Queen City
Appendix 2.1. Using Minitab for Tabular and Graphical Presentations
Appendix 2.2. Using Excel for Tabular and Graphical Presentations
Chapter 3. Descriptive Statistics: Numerical Measures
3.1. Measures of Location
Mean
Weighted Mean
Median
Geometric Mean
Mode
Percentiles
Quartiles
Exercises: Methods
Exercises: Applications
3.2. Measures of Variability
Range
Interquartile Range
Variance
Standard Deviation
Coefficient of Variation
Exercises: Methods
Exercises: Applications
3.3. Measures of Distribution Shape, Relative Location, and Detecting Outliers
Distribution Shape
z-Scores
Chebyshev’s Theorem
Empirical Rule
Detecting Outliers
Exercises: Methods
Exercises: Applications
3.4. Five-Number Summaries and Boxplots
Five-Number Summary
Box Plot
Comparative Analysis Using Boxplots
Exercises: Methods
Exercises: Applications
3.5. Measures of Association between Two Variables
Covariance
Interpretation of the Covariance
Correlation Coefficient
Interpretation of the Correlation Coefficient
Exercises: Methods
Exercises: Applications
3.6. Data Dashboards: Adding Numerical Measures to Improve Effectiveness
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem 1. Pelican Stores
Case Problem 2. Motion Picture Industry
Case Problem 3. Business Schools of Asia-Pacific
Case Problem 4. Heavenly Chocolates Website Transactions
Case Problem 5. African Elephant Populations
Appendix 3.1. Descriptive Statistics Using Minitab
Appendix 3.2. Descriptive Statistics Using Excel
Chapter 4. Introduction to Probability
4.1. Random Experiments, counting Rules, and Assigning Probabilities
Counting Rules, Combinations, and Permutations
Assigning Probabilities
Probabilities for the KP&L Project
Exercises: Methods
Exercises: Applications
4.2. Events and Their Probabilities
Exercises: Methods
Exercises: Applications
4.3. Some Basic Relationships of Probability
Complement of an Event
Addition Law
Exercises: Methods
Exercises: Applications
4.4. Conditional Probability
Independent Events
Multiplication Law
Exercises: Methods
Exercises: Applications
4.5. Bayes’ Theorem
Tabular Approach
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem. Hamilton County Judges
Chapter 5. Discrete Probability Distributions
5.1. Random Variables
Discrete Random Variables
Continuous Random Variables
Exercises: Methods
Exercises: Applications
5.2. Developing Discrete Probability Distributions
Exercises: Methods
Exercises: Applications
5.3. Expected Value and Variance
Expected Value
Variance
Exercises: Methods
Exercises: Applications
5.4. Bivariate Distributions, Covariance, and Financial Portfolios
A Bivariate Empirical Discrete Probability Distribution
Financial Applications
Summary
Exercises: Methods
5.5. Binomial Probability Distribution
A Binomial Experiment
Martin Clothing Store Problem
Using Tables of Binomial Probabilities
Expected Value and Variance for the Binomial Distribution
Exercises: Methods
Exercises: Applications
5.6. Poisson Probability Distribution
An Example Involving Time Intervals
An Example Involving Length or Distance Intervals
Exercises: Methods
Exercises: Applications
5.7. Hypergeometric Probability Distribution
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem. Go Bananas!
Appendix 5.1. Discrete Probability Distributions with Minitab
Appendix 5.2. Discrete Probability Distributions with Excel
Chapter 6. Continuous Probability Distributions
6.1. Uniform Probability Distribution
Area as a Measure of Probability
Exercises: Methods
Exercises: Applications
6.2. Normal Probability Distribution
Normal Curve
Standard Normal Probability Distribution
Computing Probabilities for Any Normal Probability Distribution
Grear Tire Company Problem
Exercises: Methods
Exercises: Applications
6.3. Normal Approximation of Binomial Probabilities
Exercises: Methods
Exercises: Applications
6.4. Exponential Probability Distribution
Computing Probabilities for the Exponential Distribution
Relationship between the Poisson and Exponential Distributions
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem. Specialty Toys
Appendix 6.1. Continuous Probability Distributions with Minitab
Appendix 6.2. Continuous Probability Distributions with Excel
Chapter 7. Sampling and Sampling Distributions
7.1. The Electronics Associates Sampling Problem
7.2. Selecting a Sample
Sampling from a Finite Population
Sampling from an Infinite Population
Exercises: Methods
Exercises: Applications
7.3. Point Estimation
Practical Advice
Exercises: Methods
Exercises: Applications
7.4. Introduction to Sampling Distributions
7.5. Sampling Distribution of x ¯
Expected Value of x ¯
Standard Deviation of x ¯
Form of the Sampling Distribution of x ¯
Sampling Distribution of x ¯ for the EAI Problem
Practical Value of the Sampling Distribution of x ¯
Relationship between the Sample Size and the Sampling Distribution of x ¯
Exercises: Methods
Exercises: Applications
7.6. Sampling Distribution of p ¯
Expected Value of p ¯
Standard Deviation of p ¯
Form of the Sampling Distribution of p ¯
Practical Value of the Sampling Distribution of p ¯
Exercises: Methods
Exercises: Applications
7.7. Properties of Point Estimators
Unbiased
Efficiency
Consistency
7.8. Other Sampling Methods
Stratified Random Sampling
Cluster Sampling
Systematic Sampling
Convenience Sampling
Judgment Sampling
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem. Marion Dairies
Appendix 7.1. The Expected Value and Standard Deviation of x ¯
Appendix 7.2. Random Sampling with Minitab
Appendix 7.3. Random Sampling with Excel
Chapter 8. Interval Estimation
8.1. Population Mean: σ Known
Margin of Error and the Interval Estimate
Practical Advice
Exercises: Methods
Exercises: Applications
8.2. Population Mean: σ Unknown
Margin of Error and the Interval Estimate
Practical Advice
Using a Small Sample
Summary of Interval Estimation Procedures
Exercises: Methods
Exercises: Applications
8.3. Determining the Sample Size
Exercises: Methods
Exercises: Applications
8.4. Population Proportion
Determining the Sample Size
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem 1. Young Professional Magazine
Case Problem 2. Gulf Real Estate Properties
Case Problem 3. Metropolitan Research, Inc.
Appendix 8.1. Interval Estimation with Minitab
Appendix 8.2. Interval Estimation Using Excel
Chapter 9. Hypothesis Tests
9.1. Developing Null and Alternative Hypotheses
The Alternative Hypothesis as a Research Hypothesis
The Null Hypothesis as an Assumption to Be Challenged
Summary of Forms for Null and Alternative Hypotheses
Exercises
9.2. Type I and Type II Errors
Exercises
9.3. Population Mean: σ Known
One-Tailed Test
Two-Tailed Test
Summary and Practical Advice
Relationship between Interval Estimation and Hypothesis Testing
Exercises
Exercises: Methods
Exercises: Applications
9.4. Population Mean: σ Unknown
One-Tailed Test
Two-Tailed Test
Summary and Practical Advice
Exercises: Methods
Exercises: Applications
9.5. Population Proportion
Summary
Exercises: Methods
Exercises: Applications
9.6. Hypothesis Testing and Decision Making
9.7. Calculating the Probability of Type II Errors
Exercises: Methods
Exercises: Applications
9.8. Determining the Sample Size for a Hypothesis Test about a Population Mean
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem 1. Quality Associates, Inc.
Case Problem 2. Ethical Behavior of Business Students at Bayview University
Appendix 9.1. Hypothesis Testing with Minitab
Appendix 9.2. Hypothesis Testing with Excel
Chapter 10. Inference about Means and Proportions with Two Populations
10.1. Inferences about the Difference between Two Population Means: σ 1 and σ 2 Known
Interval Estimation of μ 1 – μ 2
Hypothesis Tests about μ 1 – μ 2
Practical Advice
Exercises: Methods
Exercises: Applications
10.2. Inferences about the Difference between Two Population Means: σ 1 and σ 2 Unknown
Interval Estimation of μ 1 – μ 2
Hypothesis Tests about μ 1 – μ 2
Practical Advice
Exercises: Methods
Exercises: Applications
10.3. Inferences about the Difference between Two Population Means: Matched Samples
Exercises: Methods
Exercises: Applications
10.4. Inferences about the Difference between Two Population Proportions
Interval Estimation of p 1 – p 2
Hypothesis Tests about p 1 – p 2
Exercises: Methods
Exercises: Applications
Summary
Glossary
Key Formulas
Supplementary Exercises
Case Problem. Par, Inc.
Appendix 10.1. Inferences about Two Populations Using Minitab
Appendix 10.2. Inferences about Two Populations Using Excel
Chapter 11. Inferences about Population Variances
11.1. Inferences about a Population Variance
Interval Estimation
Hypothesis Testing
Exercises: Methods
Exercises: Applications
11.2. Inferences about Two Population Variances
Exercises: Methods
Exercises: Applications
Summary
Key Formulas
Supplementary Exercises
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