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Test Bank for Elementary Statistics: A Step By Step Approach 10th Edition Allan Bluman

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This is completed downloadable of Test Bank for Elementary Statistics: A Step By Step Approach, 10th Edition, Allan Bluman

 

Product Details:

  • ISBN-10 ‏ : ‎ 1259755339
  • ISBN-13 ‏ : ‎ 978-1259755330
  • Author: Allan Bluman

Al Bluman’s Elementary Statistics takes a non-theoretical approach to teaching the course. Statistics is the language of today’s world and Bluman’s market-leading Step-by-Step Approach makes it easy to learn and understand! Helping students move from the computational to the conceptual, Bluman provides all the support your students need to grasp the fundamentals of statistics and make that connection.

 

Table of Content:

  1. CHAPTER 1: The Nature of Probability and Statistics
  2. Introduction
  3. 1–1 Descriptive and Inferential Statistics
  4. 1–2 Variables and Types of Data
  5. 1–3 Data Collection and Sampling Techniques
  6. Random Sampling
  7. Systematic Sampling
  8. Stratified Sampling
  9. Cluster Sampling
  10. Other Sampling Methods
  11. 1–4 Experimental Design
  12. Observational and Experimental Studies
  13. Uses and Misuses of Statistics
  14. 1–5 Computers and Calculators
  15. Summary
  16. CHAPTER 2 Frequency Distributions and Graphs
  17. Introduction
  18. 2–1 Organizing Data
  19. Categorical Frequency Distributions
  20. Grouped Frequency Distributions
  21. 2–2 Histograms, Frequency Polygons, and Ogives
  22. The Histogram
  23. The Frequency Polygon
  24. The Ogive
  25. Relative Frequency Graphs
  26. Distribution Shapes
  27. 2–3 Other Types of Graphs
  28. Bar Graphs
  29. Pareto Charts
  30. The Time Series Graph
  31. The Pie Graph
  32. Dotplots
  33. Stem and Leaf Plots
  34. Misleading Graphs
  35. Summary
  36. CHAPTER 3 Data Description
  37. Introduction
  38. 3–1 Measures of Central Tendency
  39. The Mean
  40. The Median
  41. The Mode
  42. The Midrange
  43. The Weighted Mean
  44. Distribution Shapes
  45. 3–2 Measures of Variation
  46. Range
  47. Population Variance and Standard Deviation
  48. Sample Variance and Standard Deviation
  49. Variance and Standard Deviation for Grouped Data
  50. Coefficient of Variation
  51. Range Rule of Thumb
  52. Chebyshev’s Theorem
  53. The Empirical (Normal) Rule
  54. Linear Transformation of Data
  55. 3–3 Measures of Position
  56. Standard Scores
  57. Percentiles
  58. Quartiles and Deciles
  59. Outliers
  60. 3–4 Exploratory Data Analysis
  61. The Five-Number Summary and Boxplots
  62. Summary
  63. CHAPTER 4 Probability and Counting Rules
  64. Introduction
  65. 4–1 Sample Spaces and Probability
  66. Basic Concepts
  67. Classical Probability
  68. Complementary Events
  69. Empirical Probability
  70. Law of Large Numbers
  71. Subjective Probability
  72. Probability and Risk Taking
  73. 4–2 The Addition Rules for Probability
  74. 4–3 The Multiplication Rules and Conditional Probability
  75. The Multiplication Rules
  76. Conditional Probability
  77. Probabilities for “At Least”
  78. 4–4 Counting Rules
  79. The Fundamental Counting Rule
  80. Factorial Notation
  81. Permutations
  82. Combinations
  83. 4–5 Probability and Counting Rules
  84. Summary
  85. CHAPTER 5 Discrete Probability Distributions
  86. Introduction
  87. 5–1 Probability Distributions
  88. 5–2 Mean, Variance, Standard Deviation, and Expectation
  89. Mean
  90. Variance and Standard Deviation
  91. Expectation
  92. 5–3 The Binomial Distribution
  93. 5–4 Other Types of Distributions
  94. The Multinomial Distribution
  95. The Poisson Distribution
  96. The Hypergeometric Distribution
  97. The Geometric Distribution
  98. Summary
  99. CHAPTER 6 The Normal Distribution
  100. Introduction
  101. 6–1 Normal Distributions
  102. The Standard Normal Distribution
  103. Finding Areas Under the Standard Normal Distribution Curve
  104. A Normal Distribution Curve as a Probability Distribution Curve
  105. 6–2 Applications of the Normal Distribution
  106. Finding Data Values Given Specific Probabilities
  107. Determining Normality
  108. 6–3 The Central Limit Theorem
  109. Distribution of Sample Means
  110. Finite Population Correction Factor (Optional)
  111. 6–4 The Normal Approximation to the Binomial Distribution
  112. Summary
  113. CHAPTER 7 Confidence Intervals and Sample Size
  114. Introduction
  115. 7–1 Confidence Intervals for the Mean When σ Is Known
  116. Confidence Intervals
  117. Sample Size
  118. 7–2 Confidence Intervals for the Mean When σ Is Unknown
  119. 7–3 Confidence Intervals and Sample Size for Proportions
  120. Confidence Intervals
  121. Sample Size for Proportions
  122. 7–4 Confidence Intervals for Variances and Standard Deviations
  123. Summary
  124. CHAPTER 8 Hypothesis Testing
  125. Introduction
  126. 8–1 Steps in Hypothesis Testing—Traditional Method
  127. 8–2 z Test for a Mean
  128. P-Value Method for Hypothesis Testing
  129. 8–3 t Test for a Mean
  130. 8–4 z Test for a Proportion
  131. 8–5 χ2 Test for a Variance or Standard Deviation
  132. 8–6 Additional Topics Regarding Hypothesis Testing
  133. Confidence Intervals and Hypothesis Testing
  134. Type II Error and the Power of a Test
  135. Summary
  136. CHAPTER 9: Testing the Difference Between Two Means, Two Proportions, and Two Variances
  137. Introduction
  138. 9–1 Testing the Difference Between Two Means: Using the z Test
  139. 9–2 Testing the Difference Between Two Means of Independent Samples: Using the t Test
  140. 9–3 Testing the Difference Between Two Means: Dependent Samples
  141. 9–4 Testing the Difference Between Proportions
  142. 9–5 Testing the Difference Between Two Variances
  143. Summary
  144. CHAPTER 10: Correlation and Regression
  145. Introduction
  146. 10–1 Scatter Plots and Correlation
  147. Correlation
  148. 10–2 Regression
  149. Line of Best Fit
  150. Determination of the Regression Line Equation
  151. 10–3 Coefficient of Determination and Standard Error of the Estimate
  152. Types of Variation for the Regression Model
  153. Residual Plots
  154. Coefficient of Determination
  155. Standard Error of the Estimate
  156. Prediction Interval
  157. 10–4 Multiple Regression (Optional)
  158. The Multiple Regression Equation
  159. Testing the Significance of R
  160. Adjusted R2
  161. Summary
  162. CHAPTER 11: Other Chi-Square Tests
  163. Introduction
  164. 11–1 Test for Goodness of Fit
  165. Test of Normality (Optional)
  166. 11–2 Tests Using Contingency Tables
  167. Test for Independence
  168. Test for Homogeneity of Proportions
  169. Summary
  170. CHAPTER: 12 Analysis of Variance
  171. Introduction
  172. 12–1 One-Way Analysis of Variance
  173. 12–2 The Scheffé Test and the Tukey Test
  174. Scheffé Test
  175. Tukey Test
  176. 12–3 Two-Way Analysis of Variance
  177. Summary
  178. CHAPTER 13: Nonparametric Statistics
  179. Introduction
  180. 13–1 Advantages and Disadvantages of Nonparametric Methods
  181. Advantages
  182. Disadvantages
  183. Ranking
  184. 13–2 The Sign Test
  185. Single-Sample Sign Test
  186. Paired-Sample Sign Test
  187. 13–3 The Wilcoxon Rank Sum Test
  188. 13–4 The Wilcoxon Signed-Rank Test
  189. 13–5 The Kruskal-Wallis Test
  190. 13–6 The Spearman Rank Correlation Coefficient and the Runs Test
  191. Rank Correlation Coefficient
  192. The Runs Test
  193. Summary
  194. CHAPTER 14: Sampling and Simulation
  195. Introduction
  196. 14–1 Common Sampling Techniques
  197. Random Sampling
  198. Systematic Sampling
  199. Stratified Sampling
  200. Cluster Sampling
  201. Other Types of Sampling Techniques
  202. 14–2 Surveys and Questionnaire Design
  203. 14–3 Simulation Techniques and the Monte Carlo Method
  204. The Monte Carlo Method
  205. Summary
  206. APPENDICES
  207. A Tables
  208. B Data Bank
  209. C Glossary
  210. D Selected Answers
  211. Index

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