Preface |
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ix | |
About the Author |
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xv | |
Acknowledgments |
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xvii | |
Chapter 1 Introduction to the Central Textbook Example |
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1 | (8) |
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1 | (1) |
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2 | (1) |
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Current Research Needs of the Company |
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2 | (3) |
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Your Brief for the Case Example |
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5 | (1) |
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Extended Analytical Skills Needed in the Project |
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6 | (3) |
Chapter 2 Introduction to the Statistics Process |
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9 | (12) |
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Introductory Case: Big Data in the Airline Industry |
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9 | (2) |
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Introduction to the Statistics Process |
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11 | (1) |
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Step 1: Your Needs & Requirements |
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12 | (1) |
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13 | (2) |
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Step 3: Extracting Statistics from the Data |
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15 | (2) |
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Step 4: Understanding & Decision Making |
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17 | (1) |
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Summary: Challenges in the Statistics Process |
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17 | (1) |
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Advice to the Statistically Terrified |
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18 | (3) |
Chapter 3 Introduction to Data |
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21 | (12) |
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Introductory Case: Royal FrieslandCampina |
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21 | (2) |
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Brief Introduction to Samples, Populations & Data |
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23 | (4) |
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Basic Characteristics of Variables |
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27 | (6) |
Chapter 4 Data Collection & Capture |
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33 | (18) |
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33 | (1) |
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34 | (1) |
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Choose Constructs and Variable Measurements |
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35 | (8) |
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Initial Data Capture: Which Package? |
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43 | (1) |
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Dealing with Data Once It Has Been Captured |
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43 | (5) |
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Database & Data Analysis Software |
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48 | (1) |
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Some Complications in Datasets |
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48 | (3) |
Chapter 5 Introduction to SAS® |
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51 | (18) |
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Introductory Vignette: SAS On Top of the Analytics World |
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51 | (1) |
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Brief Introduction to SAS |
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52 | (1) |
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Introduction to the Textbook Materials |
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53 | (1) |
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Getting Started with SAS 9 or SAS Studio |
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53 | (16) |
Chapter 6 Basics of SAS Programs, Data Manipulation, Analysis & Reporting |
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69 | (20) |
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70 | (1) |
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70 | (2) |
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The Pre-Analysis Data Cleaning & Preparation Steps |
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72 | (1) |
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Overview of the Three Big Tasks in Business Statistics |
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73 | (1) |
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Basic Introduction to SAS Programming |
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73 | (4) |
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Major Task #1: Data Manipulation in SAS |
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77 | (6) |
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Major Task #2: Data Analysis |
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83 | (1) |
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Major Task #3: SAS Reporting through Output Formats |
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84 | (2) |
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The Visual Programmer Mode in SAS Studio |
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86 | (2) |
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88 | (1) |
Chapter 7 Descriptive Statistics: Understand your Data |
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89 | (20) |
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Introductory Case: 2007 AngloGold Ashanti Look Ahead |
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90 | (1) |
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91 | (1) |
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End Outcome of a Descriptive Statistics Analysis |
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91 | (1) |
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Getting Descriptive Statistics in SAS |
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92 | (2) |
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Statistics Measuring Centrality |
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94 | (3) |
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Basic Statistics Assessing Variable Spread |
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97 | (2) |
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Assessing Shape of a Variable's Distribution |
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99 | (5) |
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Conclusion on Descriptive Statistics |
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104 | (1) |
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Appendix A to Chapter 7: Basic Normality Statistics |
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104 | (5) |
Chapter 8 Basics of Associating Variables |
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109 | (14) |
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109 | (1) |
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What is Statistical Association? |
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110 | (1) |
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Association Does Not Mean Causation |
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110 | (1) |
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Overview of Associations for Different Variable Types |
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111 | (1) |
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Relating Continuous or Ordinal Data: Correlation & Covariance |
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112 | (7) |
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Relating Categorical Variables |
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119 | (4) |
Chapter 9 Using Basic Statistics to Check & Fix Data |
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123 | (12) |
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123 | (1) |
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Inappropriate Data Points |
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124 | (2) |
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Dealing Practically with Missing Data |
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126 | (1) |
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Checking Centrality & Spread |
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127 | (1) |
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Strange Variable Distributions |
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128 | (1) |
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Dealing Practically with Multi-Item Scales |
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128 | (7) |
Chapter 10 Introduction to Graphing in SAS |
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135 | (14) |
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135 | (1) |
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Major Graphing Procedures in SAS |
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136 | (2) |
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The PROC SGPLOT Routine in SAS |
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138 | (5) |
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Multiple Plots Simultaneously through PROC SGPANEL |
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143 | (1) |
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Business Dashboards through PROC GKPI |
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143 | (2) |
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Geographical Mapping Using PROC GMAP |
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145 | (1) |
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PROC SGSCATTER for Multiple Scatterplots |
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146 | (1) |
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Conclusion on SAS Graphing |
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147 | (2) |
Chapter 11 The Statistics Process: Fitting Models to Data |
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149 | (22) |
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149 | (2) |
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Look for Patterns in the Data (Fit) |
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151 | (13) |
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Step 3: Interpret the Pattern |
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164 | (4) |
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Summary of the Statistics Process |
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168 | (3) |
Chapter 12 Key Concepts: Size & Accuracy |
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171 | (40) |
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Illustrative Case: Pharmaceuticals I - AstraZeneca's Crestor |
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172 | (1) |
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173 | (1) |
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Issue # 1: Size of a Statistic |
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173 | (4) |
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Issue # 2: Accuracy of Statistics |
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177 | (2) |
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The Aspects of Inaccuracy |
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179 | (21) |
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Putting Statistical Size and Accuracy Together |
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200 | (2) |
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202 | (1) |
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Appendix A to Chapter 12: More on Accuracy (optional) |
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203 | (8) |
Chapter 13 Introduction to Linear Regression |
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211 | (58) |
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Illustrative Case: West Point |
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212 | (1) |
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213 | (1) |
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The Core Textbook Case Example for Chapter 13 |
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213 | (2) |
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Introduction to Linear Regression |
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215 | (2) |
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A Pictorial Walk through Regression |
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217 | (9) |
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Implementing Multiple Regression in SAS |
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226 | (1) |
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Step 1: Collect, Capture and Clean Data |
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227 | (4) |
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Step 2: Run an Initial Regression Analysis |
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231 | (2) |
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Step 3: Assess Fit and Apply Remedies If Necessary |
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233 | (24) |
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Step 4: Interpret the Regression Slopes |
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257 | (8) |
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Step 5: Reporting a Multiple Regression Result |
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265 | (1) |
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266 | (1) |
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267 | (2) |
Chapter 14 Categories Explaining a Continuous Variable: Comparing Two Means |
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269 | (16) |
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Introduction to Comparison of Categories |
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270 | (1) |
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Features of the Continuous Variable to Compare Across Categories |
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270 | (1) |
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Two Types of Categories to Compare |
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271 | (1) |
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Numbers of Categories to Compare: Two vs. More than Two |
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272 | (1) |
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Data Assumptions and Alternatives when Comparing Categories |
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273 | (2) |
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Comparing Two Means: T-Tests |
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275 | (9) |
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Comparing Means for More than Two Categories: ANOVA |
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284 | (1) |
Chapter 15 Categorical Data Distributions & Associations |
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285 | (14) |
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285 | (1) |
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Repeat: One-Way Categorical Distributions |
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286 | (1) |
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Repeat: Linking Categorical Variables Together |
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287 | (1) |
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Further Statistical Questions about Categorical Data |
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287 | (1) |
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Assessing One-Way Frequencies |
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288 | (5) |
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Tests of Categorical Variable Association |
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293 | (5) |
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Conclusion on Categorical Data Analysis |
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298 | (1) |
Chapter 16 Reporting Business Analytics |
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299 | (10) |
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Reminder - Your Brief for the Textbook Case Study |
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299 | (1) |
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Your Tasks in the Analytics and Reporting Stages |
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300 | (1) |
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Background Analyses Versus Displayed Reports for the CEO |
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300 | (8) |
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Conclusion on Business Statistics Reporting |
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308 | (1) |
Chapter 17 Business Analysis from Statistics: Introduction |
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309 | (16) |
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Case Study: Oracle South Africa |
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310 | (1) |
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311 | (1) |
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Overall Financial Extrapolation Process |
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312 | (1) |
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Step 1: Statistics Gives Level of or Change in Focal Variables |
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313 | (1) |
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Step 2: Financial Estimates of Revenue or Cost of One Unit |
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314 | (4) |
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Step 3: Combine Statistics with Per-Unit Financial Values |
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318 | (1) |
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319 | (1) |
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Steps 5 and 6: Net Profitability Calculations |
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319 | (2) |
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Some Simple Examples of Business Extrapolation |
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321 | (2) |
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Conclusion of Statistical Business Extrapolation |
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323 | (2) |
Chapter 18 Miscellaneous Business Statistics Topics |
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325 | (18) |
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326 | (1) |
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326 | (4) |
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330 | (5) |
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Machine Learning & Algorithms |
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335 | (1) |
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Simulation in Business Situations |
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336 | (4) |
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340 | (2) |
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342 | (1) |
Chapter 19 Bibliography |
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343 | (8) |
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343 | (8) |
Index |
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351 | |