Essentials of Modern Business Statistics with Microsoft Excel, 8th Edition
- Length: 816 pages
- Edition: 8
- Language: English
- Publisher: Cengage Learning
- Publication Date: 2020-01-01
- ISBN-10: 0357131622
- ISBN-13: 9780357131626
- Sales Rank: #1009705 (See Top 100 Books)
Develop a strong conceptual understanding of statistics as ESSENTIALS OF MODERN BUSINESS STATISTICS WITH MICROSOFT EXCEL, 8E balances real-world applications with an integrated focus on the latest version of Microsoft Excel. This best-selling, essentials edition clearly develops each statistical technique in an application setting. You learn to master statistical methodology with an easy-to-follow presentation of a statistical procedure followed by a discussion of how to use Excel 2019 to perform the procedure. Step-by-step instructions and screen captures ensure understanding. More than 140 new business examples, proven methods, and application exercises show how statistics provide insights into today’s business decisions and problems. A unique problem-scenario approach and new case problems demonstrate how to apply statistical methods to practical business situations.
Cover Brief Contents Contents Preface About the Authors Chapter 1: Data and Statistics 1.1 Applications in Business and Economics 1.2 Data 1.3 Data Sources 1.4 Descriptive Statistics 1.5 Statistical Inference 1.6 Statistical Analysis Using Microsoft Excel 1.7 Analytics 1.8 Big Data and Data Mining 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 2.2 Summarizing Data for a Quantitative Variable 2.3 Summarizing Data for Two Variables Using Tables 2.4 Summarizing Data for Two Variables Using Graphical Displays 2.5 Data Visualization: Best Practices in Creating Effective Graphical Displays Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Pelican Stores Case Problem 2: Movie Theater Releases Case Problem 3: Queen City Case Problem 4: Cut-Rate Machining, Inc. Chapter 3: Descriptive Statistics: Numerical Measures 3.1 Measures of Location 3.2 Measures of Variability 3.3 Measures of Distribution Shape, Relative Location, and Detecting Outliers 3.4 Five-Number Summaries and Boxplots 3.5 Measures of Association between Two Variables 3.6 Data Dashboards: Adding Numerical Measures to Improve Effectiveness Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Pelican Stores Case Problem 2: Movie Theater Releases Case Problem 3: Business Schools of Asia-Pacific Case Problem 4: Heavenly Chocolates Website Transactions Case Problem 5: African Elephant Populations Chapter 4: Introduction to Probability 4.1 Experiments, Counting Rules, and Assigning Probabilities 4.2 Events and Their Probabilities 4.3 Some Basic Relationships of Probability 4.4 Conditional Probability 4.5 Bayes' Theorem Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Hamilton County Judges Case Problem 2: Rob's Market Chapter 5: Discrete Probability Distributions 5.1 Random Variables 5.2 Developing Discrete Probability Distributions 5.3 Expected Value and Variance 5.4 Bivariate Distributions, Covariance, and Financial Portfolios 5.5 Binomial Probability Distribution 5.6 Poisson Probability Distribution 5.7 Hypergeometric Probability Distribution Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Go Bananas! Breakfast Cereal Case Problem 2: McNeil's Auto Mall Case Problem 3: Grievance Committee at Tuglar Corporation Case Problem 4: Sagittarius Casino Chapter 6: Continuous Probability Distributions 6.1 Uniform Probability Distribution 6.2 Normal Probability Distribution 6.3 Exponential Probability Distribution Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Specialty Toys Case Problem 2: Gebhardt Electronics Chapter 7: Sampling and Sampling Distributions 7.1 The Electronics Associates Sampling Problem 7.2 Selecting a Sample 7.3 Point Estimation 7.4 Introduction to Sampling Distributions 7.5 Sampling Distribution of x 7.6 Sampling Distribution of p 7.7 Other Sampling Methods 7.8 Practical Advice: Big Data and Errors in Sampling Summary Glossary Key Formulas Supplementary Exercises Case Problem: Marion Dairies Chapter 8: Interval Estimation 8.1 Population Mean: o Known 8.2 Population Mean: o Unknown 8.3 Determining the Sample Size 8.4 Population Proportion 8.5 Practical Advice: Big Data and Interval Estimation 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. Chapter 9: Hypothesis Tests 9.1 Developing Null and Alternative Hypotheses 9.2 Type I and Type II Errors 9.3 Population Mean: o Known 9.4 Population Mean: o Unknown 9.5 Population Proportion 9.6 Practical Advice: Big Data and Hypothesis Testing Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Quality Associates, Inc. Case Problem 2: Ethical Behavior of Business Students at Bayview University Chapter 10: Inference about Means and Proportions with Two Populations 10.1 Inferences about the Difference between Two Population Means: o1 and o2 Known 10.2 Inferences about the Difference betweenTwo Population Means: o1 and o2 Unknown 10.3 Inferences about the Difference between Two Population Means: Matched Samples 10.4 Inferences about the Difference between Two Population Proportions Summary Glossary Key Formulas Supplementary Exercises Case Problem: Par, Inc. Chapter 11: Inferences about Population Variances 11.1 Inferences about a Population Variance 11.2 Inferences about Two Population Variances Summary Key Formulas Supplementary Exercises Case Problem 1: Air Force Training Program Case Problem 2: Meticulous Drill & Reamer Chapter 12: Tests of Goodness of Fit, Independence, and Multiple Proportions 12.1 Goodness of Fit Test 12.2 Test of Independence 12.3 Testing for Equality of Three or More Population Proportions Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: A Bipartisan Agenda for Change Case Problem 2: Fuentes Salty Snacks, Inc. Case Problem 3: Fresno Board Games Chapter 13: Experimental Design and Analysis of Variance 13.1 An Introduction to Experimental Design and Analysis of Variance 13.2 Analysis of Variance and the Completely Randomized Design 13.3 Multiple Comparison Procedures 13.4 Randomized Block Design 13.5 Factorial Experiment Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Wentworth Medical Center Case Problem 2: Compensation for Sales Professionals Case Problem 3: TourisTopia Travel Chapter 14: Simple Linear Regression 14.1 Simple Linear Regression Model 14.2 Least Squares Method 14.3 Coefficient of Determination 14.4 Model Assumptions 14.5 Testing for Significance 14.6 Using the Estimated Regression Equation for Estimation and Prediction 14.7 Excel's Regression Tool 14.8 Residual Analysis: Validating Model Assumptions 14.9 Outliers and Influential Observations 14.10 Practical Advice: Big Data and Hypothesis Testing in Simple Linear Regression Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Measuring Stock Market Risk Case Problem 2: U.S. Department of Transportation Case Problem 3: Selecting a Point-and-Shoot Digital Camera Case Problem 4: Finding the Best Car Value Case Problem 5: Buckeye Creek Amusement Park Appendix 14.1: Calculus-Based Derivation of Least Squares Formulas Appendix 14.2: A Test for Significance Using Correlation Chapter 15: Multiple Regression 15.1 Multiple Regression Model 15.2 Least Squares Method 15.3 Multiple Coefficient of Determination 15.4 Model Assumptions 15.5 Testing for Significance 15.6 Using the Estimated Regression Equation for Estimation and Prediction 15.7 Categorical Independent Variables 15.8 Residual Analysis 15.9 Practical Advice: Big Data and Hypothesis Testing in Multiple Regression Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Consumer Research, Inc. Case Problem 2: Predicting Winnings for NASCAR Drivers Case Problem 3: Finding the Best Car Value Appendixes Appendix A: References and Bibliography Appendix B: Tables Appendix C: Summation Notation Appendix E: Microsoft Excel and Tools for Statistical Analysis Appendix F: Microsoft Excel Online and Tools for Statistical Analysis Index
Donate to keep this site alive
1. Disable the AdBlock plugin. Otherwise, you may not get any links.
2. Solve the CAPTCHA.
3. Click download link.
4. Lead to download server to download.