Solution Manual for Essentials of Modern Business Statistics with Microsoft Excel, 7th Edition, David R. Anderson

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Product details:

• ISBN-10 ‏ : ‎ 1337298352
• ISBN-13 ‏ : ‎ 978-1337298353
• Author: David R. Anderson; Dennis J. Sweeney; Thomas A. Williams

Discover an accessible introduction to business statistics as ESSENTIALS OF MODERN BUSINESS STATISTICS, 7E balances a conceptual understanding of statistics with real-world applications of statistical methodology. The book integrates Microsoft Excel 2016, providing step-by-step instructions and screen captures to help you master the latest Excel tools. Extremely reader-friendly, this edition includes numerous tools to maximize your course success, including Self-Test Exercises, margin annotations, insightful Notes and Comments, and real-world Methods and Applications exercises. Eleven new Case Problems, as well as new Statistics in Practice applications and real data examples and exercises, give you opportunities to put what you learn into practice. Additional learning resources, including MindTap and CengageNOW for online homework assistance and a complete support website, provide everything to acquire Excel 2016 skills and an understanding of business statistics.

Table of contents:

1. Chapter 1: Data and Statistics
2. Statistics In Practice: Bloomberg Businessweek
3. 1.1 Applications in Business and Economics
4. Accounting
5. Finance
6. Marketing
7. Production
8. Economics
9. Information Systems
10. 1.2 Data
11. Elements, Variables, and Observations
12. Scales of Measurement
13. Categorical and Quantitative Data
14. Cross-Sectional and Time Series Data
15. 1.3 Data Sources
16. Existing Sources
17. Observational Study
18. Experiment
19. Time and Cost Issues
20. Data Acquisition Errors
21. 1.4 Descriptive Statistics
22. 1.5 Statistical Inference
23. 1.6 Statistical Analysis Using Microsoft Excel
24. Data Sets and Excel Worksheets
25. Using Excel for Statistical Analysis
26. 1.7 Analytics
27. 1.8 Big Data and Data Mining
28. 1.9 Ethical Guidelines for Statistical Practice
29. Summary
30. Glossary
31. Supplementary Exercises
32. Chapter 2: Descriptive Statistics: Tabular and Graphical Displays
33. Statistics In Practice: Colgate-Palmolive Company
34. 2.1 Summarizing Data for a Categorical Variable
35. Frequency Distribution
36. Relative Frequency and Percent Frequency Distributions
37. Using Excel to Construct a Frequency Distribution, a Relative Frequency Distribution, and a Percent
38. Bar Charts and Pie Charts
39. Using Excel to Construct a Bar Chart and a Pie Chart
40. 2.2 Summarizing Data for a Quantitative Variable
41. Frequency Distribution
42. Relative Frequency and Percent Frequency Distributions
43. Using Excel to Construct a Frequency Distribution
44. Dot Plot
45. Histogram
46. Using Excel’s Recommended Charts Tool to Construct a Histogram
47. Cumulative Distributions
48. Stem-and-Leaf Display
49. 2.3 Summarizing Data for Two Variables Using Tables
50. Crosstabulation
51. Using Excel’s PivotTable Tool to Construct a Crosstabulation
52. Simpson’s Paradox
53. 2.4 Summarizing Data for Two Variables Using Graphical Displays
54. Scatter Diagram and Trendline
55. Using Excel to Construct a Scatter Diagram and a Trendline
56. Side-by-Side and Stacked Bar Charts
57. Using Excel’s Recommended Charts Tool to Construct Side-by-Side and Stacked Bar Charts
58. 2.5 Data Visualization: Best Practices in Creating Effective Graphical Displays
59. Creating Effective Graphical Displays
60. Choosing the Type of Graphical Display
61. Data Dashboards
62. Data Visualization in Practice: Cincinnati Zoo and Botanical Garden
63. Summary
64. Glossary
65. Key Formulas
66. Supplementary Exercises
67. Case Problem 1: Pelican Stores
68. Case Problem 2: Motion Picture Industry
69. Case Problem 3: Queen City
70. Case Problem 4: Cut-Rate Machining, Inc.
71. Chapter 3: Descriptive Statistics: Numerical Measures
72. Statistics In Practice: Small Fry Design
73. 3.1 Measures of Location
74. Mean
75. Median
76. Mode
77. Using Excel to Compute the Mean, Median, and Mode
78. Weighted Mean
79. Geometric Mean
80. Using Excel to Compute the Geometric Mean
81. Percentiles
82. Quartiles
83. Using Excel to Compute Percentiles and Quartiles
84. 3.2 Measures of Variability
85. Range
86. Interquartile Range
87. Variance
88. Standard Deviation
89. Using Excel to Compute the Sample Variance and Sample Standard Deviation
90. Coefficient of Variation
91. Using Excel’s Descriptive Statistics Tool
92. 3.3 Measures of Distribution Shape, Relative Location, and Detecting Outliers
93. Distribution Shape
94. z-Scores
95. Chebyshev’s Theorem
96. Empirical Rule
97. Detecting Outliers
98. 3.4 Five-Number Summaries and Box Plots
99. Five-Number Summary
100. Box Plot
101. Using Excel to Construct a Box Plot
102. Comparative Analysis Using Box Plots
103. Using Excel to Construct a Comparative Analysis Using Box Plots
104. 3.5 Measures of Association Between Two Variables
105. Covariance
106. Interpretation of the Covariance
107. Correlation Coefficient
108. Interpretation of the Correlation Coefficient
109. Using Excel to Compute the Sample Covariance and Sample Correlation Coefficient
110. 3.6 Data Dashboards: Adding Numerical Measures to Improve Effectiveness
111. Summary
112. Glossary
113. Key Formulas
114. Supplementary Exercises
115. Case Problem 1: Pelican Stores
116. Case Problem 2: Motion Picture Industry
117. Case Problem 3: Business Schools of Asia-Pacific
118. Case Problem 4: Heavenly Chocolates Website Transactions
119. Case Problem 5: African Elephant Populations
120. Chapter 4: Introduction to Probability
121. Statistics In Practice: National Aeronautics And Space Administration
122. 4.1 Experiments, Counting Rules, and Assigning Probabilities
123. Counting Rules, Combinations, and Permutations
124. Assigning Probabilities
125. Probabilities for the KP&L Project
126. 4.2 Events and Their Probabilities
127. 4.3 Some Basic Relationships of Probability
128. Complement of an Event
129. Addition Law
130. 4.4 Conditional Probability
131. Independent Events
132. Multiplication Law
133. 4.5 Bayes’ Theorem
134. Tabular Approach
135. Summary
136. Glossary
137. Key Formulas
138. Supplementary Exercises
139. Case Problem 1: Hamilton County Judges
140. Case Problem 2: Rob’s Market
141. Chapter 5: Discrete Probability Distributions
142. Statistics In Practice: Citibank
143. 5.1 Random Variables
144. Discrete Random Variables
145. Continuous Random Variables
146. 5.2 Developing Discrete Probability Distributions
147. 5.3 Expected Value and Variance
148. Expected Value
149. Variance
150. Using Excel to Compute the Expected Value, Variance, and Standard Deviation
151. 5.4 Bivariate Distributions, Covariance, and Financial Portfolios
152. A Bivariate Empirical Discrete Probability Distribution
153. Financial Applications
154. Summary
155. 5.5 Binomial Probability Distribution
156. A Binomial Experiment
157. Martin Clothing Store Problem
158. Using Excel to Compute Binomial Probabilities
159. Expected Value and Variance for the Binomial Distribution
160. 5.6 Poisson Probability Distribution
161. An Example Involving Time Intervals
162. An Example Involving Length or Distance Intervals
163. Using Excel to Compute Poisson Probabilities
164. 5.7 Hypergeometric Probability Distribution
165. Using Excel to Compute Hypergeometric Probabilities
166. Summary
167. Glossary
168. Key Formulas
169. Supplementary Exercises
170. Case Problem 1: Go Bananas!
171. Case Problem 2: McNeil’s Auto Mall
172. Case Problem 3: Grievance Committee at Tuglar Corporation
173. Case Problem 4: Sagittarius Casino

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