Statistics > TEST BANK > Test Bank Modern Business Statistics, 7th Edition by Anderson (All)

Test Bank for Modern Business Statistics, 7th Edition, 7e by David R. Anderson, Dennis J. Sweeney, Thomas A. Williams TEST BANK ISBN-13: 9780357131657 Full chapters included Chapter 1: Data an... d 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 between Two 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 Chapter 16: Regression Analysis: Model Building 16.1 General Linear Model 16.2 Determining When to Add or Delete Variables 16.3 Analysis of a Larger Problem 16.4 Variable Selection Procedures 16.5 Multiple Regression Approach to Experimental Design 16.6 Autocorrelation and the Durbin-Watson Test Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Analysis of LPGA Tour Statistics Case Problem 2: Rating Wines from the Piedmont Region of Italy Chapter 17: Time Series Analysis and Forecasting 17.1 Time Series Patterns 17.2 Forecast Accuracy 17.3 Moving Averages and Exponential Smoothing 17.4 Trend Projection 17.5 Seasonality and Trend 17.6 Time Series Decomposition Summary Glossary Key Formulas Supplementary Exercises Case Problem 1: Forecasting Food and Beverage Sales Case Problem 2: Forecasting Lost Sales Chapter 18: Nonparametric Methods 18.1 Sign Test 18.2 Wilcoxon Signed-Rank Test 18.3 Mann-Whitney-Wilcoxon Test 18.4 Kruskal-Wallis Test 18.5 Rank Correlation Summary Glossary Key Formulas Supplementary Exercises Case: RainOrShine.Com Chapter 19: Statistical Methods for Quality Control 19.1 Philosophies and Frameworks 19.2 Statistical Process Control 19.3 Acceptance Sampling Summary Glossary Key Formulas Supplementary Exercises Chapter 20: Decision Analysis 20.1 Problem Formulation 20.2 Decision Making with Probabilities 20.3 Decision Analysis with Sample Information 20.4 Computing Branch Probabilities Using Bayes' Theorem [Show More]

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