Statistics for Managers Using Microsoft Excel, Global Edition, 9th Edition
- Length: 753 pages
- Edition: 9
- Language: English
- Publisher: Pearson
- Publication Date: 2020-08-07
- ISBN-10: 1292338245
- ISBN-13: 9781292338248
- Sales Rank: #1301535 (See Top 100 Books)
For one-semester courses in Introduction to Business Statistics.
The gold standard in learning Microsoft Excelfor business statistics
Statistics for Managers Using Microsoft® Excel®, 9th Edition, Global Edition helps students develop the knowledge of Excel needed in future careers. The authors present statistics in the context of specific business fields, and now include a full chapter on business analytics. Guided by principles set forth by ASA’s Guidelines for Assessment and Instruction (GAISE) reports and the authors’ diverse teaching experiences, the text continues to innovate and improve the way this course is taught to students. Current data throughout gives students valuable practice analysing the types of data they will see in their professions, and the authors’ friendly writing style includes tips and learning aids throughout.
Cover A Roadmap for Selectinga Statistical Method Title Page Copyright Page About the Authors Brief Contents Contents Preface Resources for Success First Things First USING STATISTICS: “The Price of Admission” FTF.1 Think Differently About Statistics Statistics: A Way of Thinking Statistics: An Important Part of Your Business Education FTF.2 Business Analytics: The Changing Face of Statistics “Big Data” FTF.3 Starting Point for Learning Statistics Statistic Can Statistics ( pl., statistic) Lie? FTF.4 Starting Point for Using Software Using Software Properly FTF.5 Starting Point for Using Microsoft Excel More About the Excel Guide Workbooks Excel Skills That Readers Need REFERENCES KEY TERMS EXCEL GUIDE EG.1 Getting Started with Excel EG.2 Entering Data EG.3 Open or Save a Workbook EG.4 Working with a Workbook EG.5 Print a Worksheet EG.6 Reviewing Worksheets EG.7 If You Use the Workbook Instructions TABLEAU GUIDE TG.1 Getting Started with Tableau TG.2 Entering Data TG.3 Open or Save a Workbook TG.4 Working with Data TG.5 Print a Workbook 1 Defining and Collecting Data USING STATISTICS: Defining Moments 1.1 Defining Variables Classifying Variables by Type Measurement Scales 1.2 Collecting Data Populations and Samples Data Sources 1.3 Types of Sampling Methods Simple Random Sample Systematic Sample Stratified Sample Cluster Sample 1.4 Data Cleaning Invalid Variable Values Coding Errors Data Integration Errors Missing Values Algorithmic Cleaning of Extreme Numerical Values 1.5 Other Data Preprocessing Tasks Data Formatting Stacking and Unstacking Data Recoding Variables 1.6 Types of Survey Errors Coverage Error Nonresponse Error Sampling Error Measurement Error Ethical Issues About Surveys CONSIDER THIS: New Media Surveys/Old Survey Errors USING STATISTICS: Defining Moments, Revisited SUMMARY REFERENCES KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR Chapter 1 Managing Ashland MultiComm Services CardioGood Fitness Clear Mountain State Student Survey Learning With the Digital Cases Chapter 1 EXCEL GUIDE EG1.1 Defining Variables EG1.2 Types of Sampling Methods EG1.3 Data Cleaning EG1.4 Other Data Preprocessing Chapter 1 TABLEAU GUIDE TG1.1 Defining Variables TG1.2 Data Cleaning 2 Organizing and Visualizing Variables USING STATISTICS: “The Choice Is Yours” 2.1 Organizing Categorical Variables The Summary Table The Contingency Table 2.2 Organizing Numerical Variables The Frequency Distribution The Relative Frequency Distribution and the Percentage Distribution The Cumulative Distribution 2.3 Visualizing Categorical Variables The Bar Chart The Pie Chart and the Doughnut Chart The Pareto Chart Visualizing Two Categorical Variables 2.4 Visualizing Numerical Variables The Stem-and-Leaf Display The Histogram The Percentage Polygon The Cumulative Percentage Polygon (Ogive) 2.5 Visualizing Two Numerical Variables The Scatter Plot The Time-Series Plot 2.6 Organizing a Mix of Variables Drill-Down 2.7 Visualizing a Mix of Variables Colored Scatter Plot (Tableau) Bubble Chart PivotChart Treemap Sparklines 2.8 Filtering and Querying Data Excel Slicers 2.9 Pitfalls in Organizing and Visualizing Variables Obscuring Data Creating False Impressions Chartjunk USING STATISTICS: “The Choice Is Yours,” Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR Chapter 2 Managing Ashland MultiComm Services Digital Case CardioGood Fitness The Choice Is Yours Follow-Up Clear Mountain State Student Survey Chapter 2 EXCEL GUIDE EG2.1 Organizing Categorical Variables EG2.2 Organizing Numerical Variables EG2.3 Visualizing Categorical Variables EG2.4 Visualizing Numerical Variables EG2.5 Visualizing Two Numerical Variables EG2.6 Organizing a Mix of Variables EG2.7 Visualizing a Mix of Variables EG2.8 Filtering and Querying Data Chapter 2 TABLEAU GUIDE TG2.1 Organizing Categorical Variables TG2.2 Organizing Numerical Variables TG2.3 Visualizing Categorical Variables TG2.4 Visualizing Numerical Variables TG2.5 Visualizing Two Numerical Variables TG2.6 Organizing a Mix of Variables TG2.7 Visualizing a Mix of Variables 3 Numerical Descriptive Measures USING STATISTICS: More Descriptive Choices 3.1 Measures of Central Tendency The Mean The Median The Mode The Geometric Mean 3.2 Measures of Variation and Shape The Range The Variance and the Standard Deviation The Coefficient of Variation Z Scores Shape: Skewness Shape: Kurtosis 3.3 Exploring Numerical Variables Quartiles The Interquartile Range The Five-Number Summary The Boxplot 3.4 Numerical Descriptive Measures for a Population The Population Mean The Population Variance and Standard Deviation The Empirical Rule Chebyshev’s Theorem 3.5 The Covariance and the Coefficient of Correlation The Covariance The Coefficient of Correlation 3.6 Descriptive Statistics: Pitfalls and Ethical Issues USING STATISTICS: More Descriptive Choices, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR Chapter 3 Managing Ashland MultiComm Services Digital Case CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Chapter 3 EXCEL GUIDE EG3.1 Measures of Central Tendency EG3.2 Measures of Variation and Shape EG3.3 Exploring Numerical Variables EG3.4 Numerical Descriptive Measures for a Population EG3.5 The Covariance and the Coefficient of Correlation Chapter 3 TABLEAU GUIDE TG3.1 Exploring Numerical Variables 4 Basic Probability USING STATISTICS: Probable Outcomes at Fredco Warehouse Club 4.1 Basic Probability Concepts Events and Sample Spaces Types of Probability Summarizing Sample Spaces Simple Probability Joint Probability Marginal Probability General Addition Rule 4.2 Conditional Probability Calculating Conditional Probabilities Decision Trees Independence Multiplication Rules Marginal Probability Using the General Multiplication Rule 4.3 Ethical Issues and Probability 4.4 Bayes’ Theorem CONSIDER THIS: Divine Providence and Spam 4.5 Counting Rules USING STATISTICS: Probable Outcomes at Fredco Warehouse Club, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 4 Digital Case CardioGood Fitness The Choice Is Yours Follow-Up Clear Mountain State Student Survey Chapter 4 EXCEL GUIDE EG4.1 Basic Probability Concepts EG4.2 Bayes’ Theorem 5 Discrete Probability Distributions USING STATISTICS: Events of Interest at Ricknel Home Centers 5.1 The Probability Distribution for a Discrete Variable Expected Value of a Discrete Variable Variance and Standard Deviation of a Discrete Variable 5.2 Binomial Distribution Histograms for Discrete Variables Summary Measures for the Binomial Distribution 5.3 Poisson Distribution 5.4 Covariance of a Probability Distribution and its Application in Finance 5.5 Hypergeometric Distribution USING STATISTICS: Events of Interest ..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR Chapter 5 Managing Ashland MultiComm Services Digital Case Chapter 5 EXCEL GUIDE EG5.1 The Probability Distribution for a Discrete Variable EG5.2 Binomial Distribution EG5.3 Poisson Distribution 6 The Normal Distribution and Other Continuous Distributions USING STATISTICS: Normal Load Times at MyTVLab 6.1 Continuous Probability Distributions 6.2 The Normal Distribution Role of the Mean and the Standard Deviation Calculating Normal Probabilities VISUAL EXPLORATIONS: Exploring the Normal Distribution Finding X Values CONSIDER THIS: What Is Normal? 6.3 Evaluating Normality Comparing Data Characteristics to Theoretical Properties Constructing the Normal Probability Plot 6.4 The Uniform Distribution 6.5 The Exponential Distribution 6.6 The Normal Approximation to the Binomial Distribution USING STATISTICS: Normal Load Times ..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 6 Managing Ashland MultiComm Services CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Digital Case Chapter 6 EXCEL GUIDE EG6.1 The Normal Distribution EG6.2 Evaluating Normality 7 Sampling Distributions USING STATISTICS: Sampling Oxford Cereals 7.1 Sampling Distributions 7.2 Sampling Distribution of the Mean The Unbiased Property of the Sample Mean Standard Error of the Mean Sampling from Normally Distributed Populations Sampling from Non-Normally Distributed Populations—The Central Limit Theorem VISUAL EXPLORATIONS: Exploring Sampling Distributions 7.3 Sampling Distribution of the Proportion 7.4 Sampling from Finite Populations USING STATISTICS: Sampling Oxford Cereals, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 7 Managing Ashland MultiComm Services Digital Case Chapter 7 EXCEL GUIDE EG7.1 Sampling Distribution of the Mean 8 Confidence Interval Estimation USING STATISTICS: Getting Estimates at Ricknel Home Centers 8.1 Confidence Interval Estimate for the Mean (σ Known) Sampling Error Can You Ever Know the Population Standard Deviation? 8.2 Confidence Interval Estimate for the Mean (σ Unknown) Student’s t Distribution The Concept of Degrees of Freedom Properties of the t Distribution The Confidence Interval Statement 8.3 Confidence Interval Estimate for the Proportion 8.4 Determining Sample Size Sample Size Determination for the Mean Sample Size Determination for the Proportion 8.5 Confidence Interval Estimation and Ethical Issues 8.6 Application of Confidence Interval Estimation in Auditing 8.7 Estimation and Sample Size Determination for Finite Populations 8.8 Bootstrapping USING STATISTICS: Getting Estimates at Ricknel Home Centers, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 8 Managing Ashland MultiComm Services Digital Case Sure Value Convenience Stores CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Chapter 8 EXCEL GUIDE EG8.1 Confidence Interval Estimate for the Mean (σ Known) EG8.2 Confidence Interval Estimate for the Mean (σ Unknown) EG8.3 Confidence Interval Estimate for the Proportion EG8.4 Determining Sample Size 9 Fundamentals of Hypothesis Testing: One-Sample Tests USING STATISTICS: Significant Testing at Oxford Cereals 9.1 Fundamentals of Hypothesis Testing The Critical Value of the Test Statistic Regions of Rejection and Nonrejection Risks in Decision Making Using Hypothesis Testing Z Test for the Mean (σ Known) Hypothesis Testing Using the Critical Value Approach Hypothesis Testing Using the p-Value Approach A Connection Between Confidence Interval Estimation and Hypothesis Testing Can You Ever Know the Population Standard Deviation? 9.2 t Test of Hypothesis for the Mean (σ Unknown) Using the Critical Value Approach Using the p-Value Approach Checking the Normality Assumption 9.3 One-Tail Tests Using the Critical Value Approach Using the p-Value Approach 9.4 Z Test of Hypothesis for the Proportion Using the Critical Value Approach Using the p-Value Approach 9.5 Potential Hypothesis-Testing Pitfalls and Ethical Issues Important Planning Stage Questions Statistical Significance Versus Practical Significance Statistical Insignificance Versus Importance Reporting of Findings Ethical Issues 9.6 Power of the Test USING STATISTICS: Significant Testing ..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 9 Managing Ashland MultiComm Services Digital Case Sure Value Convenience Stores Chapter 9 EXCEL GUIDE EG9.1 Fundamentals of Hypothesis Testing EG9.2 t Test of Hypothesis for the Mean (σ Unknown) EG9.3 One-Tail Tests EG9.4 Z Test of Hypothesis for the Proportion 10 Two-Sample Tests USING STATISTICS: Differing Means for Selling Streaming Media Players at Arlingtons? 10.1 Comparing the Means of Two Independent Populations Pooled-Variance t Test for the Difference Between Two Means Assuming Equal Variances Evaluating the Normality Assumption Confidence Interval Estimate for the Difference Between Two Means Separate-Variance t Test for the Difference Between Two Means, Assuming Unequal Variances CONSIDER THIS: Do People Really Do This? 10.2 Comparing the Means of Two Related Populations Paired t Test Confidence Interval Estimate for the Mean Difference 10.3 Comparing the Proportions of Two Independent Populations Z Test for the Difference Between Two Proportions Confidence Interval Estimate for the Difference Between Two Proportions 10.4 F Test for the Ratio of Two Variances 10.5 Effect Size USING STATISTICS: Differing Means for Selling..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 10 Managing Ashland MultiComm Services Digital Case Sure Value Convenience Stores CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Chapter 10 EXCEL GUIDE EG10.1 Comparing the Means of Two Independent Populations EG10.2 Comparing the Means of Two Related Populations EG10.3 Comparing the Proportions of Two Independent Populations EG10.4 F Test for the Ratio of Two Variances 11 Analysis of Variance USING STATISTICS: The Means to Find Differences at Arlingtons 11.1 One-Way ANOVA F Test for Differences Among More Than Two Means One-Way ANOVA F Test Assumptions Levene Test for Homogeneity of Variance Multiple Comparisons: The Tukey-Kramer Procedure 11.2 Two-Way ANOVA Factor and Interaction Effects Testing for Factor and Interaction Effects Multiple Comparisons: The Tukey Procedure Visualizing Interaction Effects: The Cell Means Plot Interpreting Interaction Effects 11.3 The Randomized Block Design 11.4 Fixed Effects, Random Effects, and Mixed Effects Models USING STATISTICS: The Means to Find Differences at Arlingtons, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 11 Managing Ashland MultiComm Services PHASE 1 PHASE 2 Digital Case Sure Value Convenience Stores CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Chapter 11 EXCEL GUIDE EG11.1 The Completely Randomized Design: One-Way Anova EG11.2 The Factorial Design: Two-Way Anova 12 Chi-Square and Nonparametric Tests USING STATISTICS: Avoiding Guesswork About Resort Guests 12.1 Chi-Square Test for the Difference Between Two Proportions 12.2 Chi-Square Test for Differences Among More Than Two Proportions The Marascuilo Procedure The Analysis of Proportions (ANOP) 12.3 Chi-Square Test of Independence 12.4 Wilcoxon Rank Sum Test for Two Independent Populations 12.5 Kruskal-Wallis Rank Test for the One-Way ANOVA Assumptions of the Kruskal-Wallis Rank Test 12.6 McNemar Test for the Difference Between Two Proportions (Related Samples\ 12.7 Chi-Square Test for the Variance or Standard Deviation 12.8 Wilcoxon Signed Ranks Test for Two Related Populations USING STATISTICS: Avoiding Guesswork ..., Revisited REFERENCES SUMMARY KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 12 Managing Ashland MultiComm Services PHASE 1 PHASE 2 Digital Case Sure Value Convenience Stores CardioGood Fitness More Descriptive Choices Follow-Up Clear Mountain State Student Survey Chapter 12 EXCEL GUIDE EG12.1 Chi-Square Test for the Difference Between Two Proportions EG12.2 Chi-Square Test for Differences Among More Than Two Proportions EG12.3 Chi-Square Test of Independence EG12.4 Wilcoxon Rank Sum Test: A Nonparametric Method for Two Independent Populations EG12.5 Kruskal-Wallis Rank Test: A Nonparametric Method for the One-Way Anova 13 Simple Linear Regression USING STATISTICS: Knowing Customers at Sunflowers Apparel Preliminary Analysis 13.1 Simple Linear Regression Models 13.2 Determining the Simple Linear Regression Equation The Least-Squares Method Predictions in Regression Analysis: Interpolation Versus Extrapolation Calculating the Slope, b1, and the Y Intercept, b0 VISUAL EXPLORATIONS: Exploring Simple Linear Regression Coefficients 13.3 Measures of Variation Computing the Sum of Squares The Coefficient of Determination Standard Error of the Estimate 13.4 Assumptions of Regression 13.5 Residual Analysis Evaluating the Assumptions 13.6 Measuring Autocorrelation: The Durbin-Watson Statistic Residual Plots to Detect Autocorrelation The Durbin-Watson Statistic 13.7 Inferences About the Slope and Correlation Coefficient t Test for the Slope F Test for the Slope Confidence Interval Estimate for the Slope t Test for the Correlation Coefficient 13.8 Estimation of Mean Values and Prediction of Individual Values The Confidence Interval Estimatefor the Mean Response The Prediction Interval for an Individual Response 13.9 Potential Pitfalls in Regression USING STATISTICS: Knowing Customers ..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 13 Managing Ashland MultiComm Services Digital Case Brynne Packaging Chapter 13 EXCEL GUIDE EG13.1 Determining the Simple Linear Regression Equation EG13.2 Measures of Variation EG13.3 Residual Analysis EG13.4 Measuring Autocorrelation: the Durbin-Watson Statistic EG13.5 Inferences About the Slope and Correlation Coefficient EG13.6 Estimation of Mean Values and Prediction of Individual Values Chapter 13 TABLEAU GUIDE TG13.1 Determining the Simple Linear Regression Equation TG13.2 Measures of Variation 14 Introduction to Multiple Regression USING STATISTICS: The Multiple Effects of OmniPower Bars 14.1 Developing a Multiple Regression Model Interpreting the Regression Coefficients Predicting the Dependent Variable Y 14.2 Evaluating Multiple Regression Models Coefficient of Multiple Determination, r 2 Adjusted r 2 F Test for the Significance of the Overall Multiple Regression Model 14.3 Multiple Regression Residual Analysis 14.4 Inferences About the Population Regression Coefficients Tests of Hypothesis Confidence Interval Estimation 14.5 Testing Portions of the Multiple Regression Model Coefficients of Partial Determination 14.6 Using Dummy Variables and Interaction Terms Interactions CONSIDER THIS: What Is Not Normal? (Using a Categorical Dependent Variable) 14.7 Logistic Regression 14.8 Cross-Validation USING STATISTICS: The Multiple Effects …, Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 14 Managing Ashland MultiComm Services Digital Case CHAPTER 14 EXCEL GUIDE EG14.1 Developing a Multiple Regression Model EG14.2 Evaluating Multiple Regression Models EG14.3 Multiple Regression Residual Analysis EG14.4 Inferences About the Population Regression Coefficients EG14.5 Testing Portions of the Multiple Regression Model EG14.6 Using Dummy Variables and Interaction Terms EG14.7 Logistic Regression 15 Multiple Regression Model Building USING STATISTICS: Valuing Parsimony at WSTA-TV 15.1 The Quadratic Regression Model Finding the Regression Coefficients and Predicting Y Testing for the Significance of the Quadratic Model Testing the Quadratic Effect The Coefficient of Multiple Determination 15.2 Using Transformations in Regression Models The Square-Root Transformation The Log Transformation 15.3 Collinearity 15.4 Model Building The Stepwise Regression Approach to Model Building The Best Subsets Approach to Model Building 15.5 Pitfalls in Multiple Regression and Ethical Issues Pitfalls in Multiple Regression Ethical Issues USING STATISTICS: Valuing Parsimony ..., Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 15 The Mountain States Potato Company Sure Value Convenience Stores Digital Case The Craybill Instrumentation Company Case More Descriptive Choices Follow-Up Chapter 15 EXCEL GUIDE EG15.1 The Quadratic Regression Model EG15.2 Using Transformations in Regression Models EG15.3 Collinearity EG15.4 Model Building 16 Time-Series Forecasting USING STATISTICS: Is the ByYourDoor Service Trending? 16.1 Time-Series Component Factors 16.2 Smoothing an Annual Time Series Moving Averages Exponential Smoothing 16.3 Least-Squares Trend Fitting and Forecasting The Linear Trend Model The Quadratic Trend Model The Exponential Trend Model Model Selection Using First, Second,and Percentage Differences 16.4 Autoregressive Modeling for Trend Fitting and Forecasting Selecting an Appropriate Autoregressive Model Determining the Appropriateness of a Selected Model 16.5 Choosing an Appropriate Forecasting Model Residual Analysis The Magnitude of the Residuals Through Squared or Absolute Differences The Principle of Parsimony A Comparison of Four Forecasting Methods 16.6 Time-Series Forecasting of Seasonal Data Least-Squares Forecasting with Monthly or Quarterly Data 16.7 Index Numbers CONSIDER THIS: Let the Model User Beware USING STATISTICS: Is the ByYourDoor Service Trending? Revisited SUMMARY REFERENCES KEY EQUATIONS KEY TERMS CHECKING YOUR UNDERSTANDING CHAPTER REVIEW PROBLEMS CASES FOR CHAPTER 16 Managing Ashland MultiComm Services Digital Case CHAPTER 16 EXCEL GUIDE EG16.1 Smoothing an Annual Time Series EG16.2 Least-Squares Trend Fitting and Forecasting EG16.3 Autoregressive Modeling for Trend Fitting and Forecasting EG16.4 Choosing an Appropriate Forecasting Model EG16.5 Time-Series Forecasting of Seasonal Data 17 Business Analytics USING STATISTICS: Back to Arlingtons for the Future 17.1 Business Analytics Overview Business Analytics Categories Business Analytics Vocabulary CONSIDER THIS: What’s My Major If I Want to Be a Data Miner? Inferential Statistics and Predictive Analytics Microsoft Excel and Business Analytics Remainder of This Chapter 17.2 Descriptive Analytics Dashboards Data Dimensionality and Descriptive Analytics 17.3 Decision Trees Regression Trees Classification Trees Subjectivity and Interpretation 17.4 Clustering 17.5 Association Analysis 17.6 Text Analytics 17.7 Prescriptive Analytics Optimization and Simulation USING STATISTICS: Back to Arlingtons ..., Revisited REFERENCES KEY TERMS CHECKING YOUR UNDERSTANDING Chapter 17 SOFTWARE GUIDE SG17.1 Descriptive Analytics SG17.2 Predictive Analytics for Clustering 18 Getting Ready to Analyze Data in the Future USING STATISTICS: Mounting Future Analyses 18.1 Analyzing Numerical Variables Describe the Characteristics of a Numerical Variable Reach Conclusions About the Population Mean or the Standard Deviation Determine Whether the Mean and/or Standard Deviation Differs Depending on the Group Determine Which Factors Affect the Value of a Variable Predict the Value of a Variable Based on the Values of Other Variables Classify or Associate Items Determine Whether the Values of a Variable Are Stable Over Time 18.2 Analyzing Categorical Variables Describe the Proportion of Items of Interest in Each Category Reach Conclusions About the Proportion of Items of Interest Determine Whether the Proportion of Items of Interest Differs Depending on the Group Predict the Proportion of Items of Interest Based on the Values of Other Variables Cluster or Associate Items Determine Whether the Proportion of Items of Interest Is Stable Over Time USING STATISTICS: The Future to Be Visited CHAPTER REVIEW PROBLEMS Appendices A. Basic Math Concepts and Symbols A.1 Operators A.2 Rules for Arithmetic Operations A.3 Rules for Algebra: Exponents and Square Roots A.4 Rules for Logarithms A.5 Summation Notation A.6 Greek Alphabet B. Important Software Skills and Concepts B.1 Identifying the Software Version B.2 Formulas B.3 Excel Cell References B.4 Excel Worksheet Formatting B.5E Excel Chart Formatting B.5T Tableau Chart Formatting B.6 Creating Histograms for Discrete Probability Distributions (Excel\ B.7 Deleting the “Extra” Histogram Bar (Excel) C. Online Resources C.1 About the Online Resources for This Book C.2 Data Files C.3 Microsoft Excel Files Integrated With This Book C.4 Supplemental Files D. Configuring Software D.1 Microsoft Excel Configuration D.2 Supplemental Files E. Table E.1 Table of Random Numbers E.2 The Cumulative Standardized Normal Distribution E.3 Critical Values of t E.4 Critical Values of x² E.5 Critical Values of F E.6 Lower and Upper Critical Values, T1, of the Wilcoxon Rank Sum Test E.7 Critical Values of the Studentized Range, Q E.8 Critical Values, dL and dU, of the Durbin-Watson Statistic, D (Critical Values Are One-Sided\ E.9 Control Chart Factors E.10 The Standardized Normal Distribution F. Useful Knowledge F.1 Keyboard Shortcuts F.2 Understanding the Nonstatistical Excel Functions G. Software FAQs G.1 Microsoft Excel FAQs G.2 PHStat FAQs G.3 Tableau FAQs H. All About PHStat H.1 What is PHStat? H.2 Obtaining and Setting Up PHStat H.3 Using PHStat H.4 PHStat Procedures, by Category Self-Test Solutions and Answers to Selected Even-Numbered Problems Index A B C D E F G H I J K L M N O P Q R S T U V W Y Z Credits
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