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Test Bank for Social Statistics for a Diverse Society Seventh Edition

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Test Bank for Social Statistics for a Diverse Society Seventh Edition

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Today’s students live in a world characterized by a growing diversity and richness of social differences. In the seventh edition of Social Statistics for a Diverse Society, authors Chava Frankfort-Nachmias and Anna Leon-Guerrero continue to help students learn statistics through real research examples related to the dynamic interplay of race, class, gender, and other social variables. Focusing on the constant intersections between local and global social concerns and methods of inquiry and investigation, this new edition continues to emphasize intuition and common sense while demonstrating the link between the practice of statistics and important social issues. In addition, guides for reading and interpreting the research literature help students understand key statistical concepts, while SPSS demonstrations and a rich variety of exercises help them hone their problem-solving skills.

 

Table of Content:

  1. CHAPTER 1 • The What and the Why of Statistics
  2. The Research Process
  3. Asking Research Questions
  4. The Role of Theory
  5. Formulating the Hypotheses
  6. Independent and Dependent Variables: Causality
  7. Independent and Dependent Variables: Guidelines
  8. Collecting Data
  9. Levels of Measurement
  10. Nominal Level of Measurement
  11. Ordinal Level of Measurement
  12. Interval-Ratio Level of Measurement
  13. Cumulative Property of Levels of Measurement
  14. Levels of Measurement of Dichotomous Variables
  15. Discrete and Continuous Variables
  16. → A Closer Look 1.1: A Cautionary Note: Measurement Error
  17. Analyzing Data and Evaluating the Hypotheses
  18. Descriptive and Inferential Statistics
  19. Evaluating the Hypotheses
  20. Examining a Diverse Society
  21. → A Closer Look 1.2: A Tale of Simple Arithmetic: How Culture May Influence How We Count
  22. Learning Statistics
  23. → Data at Work
  24. CHAPTER 2 • The Organization and Graphic Presentation of Data
  25. Frequency Distributions
  26. Proportions and Percentages
  27. Percentage Distributions
  28. The Construction of Frequency Distributions
  29. Frequency Distributions for Nominal Variables
  30. Frequency Distributions for Ordinal Variables
  31. Frequency Distributions for Interval-Ratio Variables
  32. Cumulative Distributions
  33. → A Closer Look 2.1: Real Limits, Stated Limits, and Midpoints of Class Intervals
  34. Rates
  35. Reading the Research Literature: Access to Public Benefits
  36. Graphic Presentation of Data
  37. The Pie Chart
  38. The Bar Graph
  39. The Histogram
  40. The Statistical Map
  41. The Line Graph
  42. The Time-Series Chart
  43. Statistics in Practice: Foreign-Born Population 65 Years and Over
  44. → A Closer Look 2.2: A Cautionary Note: Distortions in Graphs
  45. → Data at Work: Kurt Taylor Gaubatz: Graduate Program in International Studies
  46. CHAPTER 3 • Measures of Central Tendency
  47. The Mode
  48. The Median
  49. Finding the Median in Sorted Data
  50. An Odd Number of Cases
  51. An Even Number of Cases
  52. Finding the Median in Frequency Distributions
  53. Locating Percentiles in a Frequency Distribution
  54. The Mean
  55. → A Closer Look 3.1: Finding the Mean in a Frequency Distribution
  56. Understanding Some Important Properties of the Arithmetic Mean
  57. Interval-Ratio Level of Measurement
  58. Center of Gravity
  59. Sensitivity to Extremes
  60. Reading the Research Literature: The Case of Reporting Income
  61. Statistics in Practice: The Shape of the Distribution
  62. The Symmetrical Distribution
  63. The Positively Skewed Distribution
  64. The Negatively Skewed Distribution
  65. Guidelines for Identifying the Shape of a Distribution
  66. → A Closer Look 3.2: A Cautionary Note: Representing Income
  67. Considerations for Choosing a Measure of Central Tendency
  68. Level of Measurement
  69. Skewed Distribution
  70. Symmetrical Distribution
  71. → Data at Work: Ben Anderstone: Political Consultant
  72. CHAPTER 4 • Measures of Variability
  73. The Importance of Measuring Variability
  74. The Index of Qualitative Variation
  75. Steps for Calculating the IQV
  76. Expressing the IQV as a Percentage
  77. Statistics in Practice: Diversity in U.S. Society
  78. The Range
  79. The Interquartile Range
  80. The Box Plot
  81. The Variance and the Standard Deviation
  82. Calculating the Deviation From the Mean
  83. Calculating the Variance and the Standard Deviation
  84. Considerations for Choosing a Measure of Variation
  85. → A Closer Look 4.1: More on Interpreting the Standard Deviation
  86. Reading the Research Literature: Community College Mentoring
  87. → Data at Work: Sruthi Chandrasekaran: Senior Research Associate
  88. CHAPTER 5 • The Normal Distribution
  89. Properties of the Normal Distribution
  90. Empirical Distributions Approximating the Normal Distribution
  91. Areas Under the Normal Curve
  92. Interpreting the Standard Deviation
  93. An Application of the Normal Curve
  94. Transforming a Raw Score Into a Z Score
  95. The Standard Normal Distribution
  96. The Standard Normal Table
  97. 1. Finding the Area Between the Mean and a Positive or Negative Z Score
  98. 2. Finding the Area Above a Positive Z Score or Below a Negative Z Score
  99. 3. Transforming Proportions and Percentages Into Z Scores
  100. Finding a Z Score That Bounds an Area Above It
  101. Finding a Z Score That Bounds an Area Below It
  102. 4. Working With Percentiles in a Normal Distribution
  103. Finding the Percentile Rank of a Score Higher Than the Mean
  104. Finding the Percentile Rank of a Score Lower Than the Mean
  105. Finding the Raw Score Associated With a Percentile Higher Than 50
  106. Finding the Raw Score Associated With a Percentile Lower Than 50
  107. Reading the Research Literature: Child Health and Academic Achievement
  108. → A Closer Look 5.1: Percentages, Proportions, and Probabilities
  109. → Data at Work: Claire Wulf Winiarek: Director of Collaborative Policy Engagement
  110. CHAPTER 6 • Sampling and Sampling Distributions
  111. Aims of Sampling
  112. Basic Probability Principles
  113. Probability Sampling
  114. The Simple Random Sample
  115. The Systematic Random Sample
  116. The Stratified Random Sample
  117. The Concept of the Sampling Distribution
  118. The Population
  119. → A Closer Look 6.1: Disproportionate Stratified Samples and Diversity
  120. The Sample
  121. The Dilemma
  122. The Sampling Distribution
  123. The Sampling Distribution of the Mean
  124. An Illustration
  125. Review
  126. The Mean of the Sampling Distribution
  127. The Standard Error of the Mean
  128. The Central Limit Theorem
  129. The Size of the Sample
  130. The Significance of the Sampling Distribution and the Central Limit Theorem
  131. Statistics in Practice: The 2016 U.S. Presidential Election
  132. → Data at Work: Emily Treichler: Postdoctoral Fellow
  133. CHAPTER 7 • Estimation
  134. Point and Interval Estimation
  135. Confidence Intervals for Means
  136. → A Closer Look 7.1: Estimation as a Type Inference
  137. Determining the Confidence Interval
  138. Calculating the Standard Error of the Mean
  139. Deciding on the Level of Confidence and Finding the Corresponding Z Value
  140. Calculating the Confidence Interval
  141. Interpreting the Results
  142. Reducing Risk
  143. Estimating Sigma
  144. Calculating the Estimated Standard Error of the Mean
  145. Deciding on the Level of Confidence and Finding the Corresponding Z Value
  146. Calculating the Confidence Interval
  147. Interpreting the Results
  148. Sample Size and Confidence Intervals
  149. Statistics in Practice: Hispanic Migration and Earnings
  150. → A Closer Look 7.2: What Affects Confidence Interval Width?
  151. Confidence Intervals for Proportions
  152. Determining the Confidence Interval
  153. Calculating the Estimated Standard Error of the Proportion
  154. Deciding on the Desired Level of Confidence and Finding the Corresponding Z Value
  155. Calculating the Confidence Interval
  156. Interpreting the Results
  157. Reading the Research Literature: Women Victims of Intimate Violence
  158. → Data at Work: Laurel Person Mecca: Research Specialist
  159. CHAPTER 8 • Testing Hypotheses
  160. Assumptions of Statistical Hypothesis Testing
  161. Stating the Research and Null Hypotheses
  162. The Research Hypothesis (H1)
  163. The Null Hypothesis (H0)
  164. Probability Values and Alpha
  165. → A Closer Look 8.1: More About Significance
  166. The Five Steps in Hypothesis Testing: A Summary
  167. Errors in Hypothesis Testing
  168. The t Statistic and Estimating the Standard Error
  169. The t Distribution and Degrees of Freedom
  170. Comparing the t and Z Statistics
  171. Hypothesis Testing With One Sample and Population Variance Unknown
  172. Hypothesis Testing With Two Sample Means
  173. The Assumption of Independent Samples
  174. Stating the Research and Null Hypotheses
  175. The Sampling Distribution of the Difference Between Means
  176. Estimating the Standard Error
  177. Calculating the Estimated Standard Error
  178. The t Statistic
  179. Calculating the Degrees of Freedom for a Difference Between Means Test
  180. The Five Steps in Hypothesis Testing About Difference Between Means: A Summary
  181. → A Closer Look 8.2: Calculating the Estimated Standard Error and the Degrees of Freedom (df) When the Population Variances Are Assumed to Be Unequal
  182. Statistics in Practice: Vape Use Among Teens
  183. Hypothesis Testing With Two Sample Proportions
  184. Reading the Research Literature: Reporting the Results of Hypothesis Testing
  185. → Data at Work: Stephanie Wood: Campus Visit Coordinator
  186. CHAPTER 9 • Bivariate Tables
  187. How to Construct a Bivariate Table
  188. How to Compute Percentages in a Bivariate Table
  189. Calculating Percentages Within Each Category of the Independent Variable
  190. Comparing the Percentages Across Different Categories of the Independent Variable
  191. → A Closer Look 9.1: How to Deal With Ambiguous Relationships Between Variables
  192. Reading the Research Literature: Racial Disparities and Educational Attainment
  193. The Properties of a Bivariate Relationship
  194. The Existence of the Relationship
  195. The Strength of the Relationship
  196. The Direction of the Relationship
  197. Elaboration
  198. Testing for Nonspuriousness: Firefighters and Property Damage
  199. An Intervening Relationship: Religion and Attitude Toward Abortion
  200. Conditional Relationships: More on Abortion
  201. The Limitations of Elaboration
  202. Reading the Research Literature: The Digital Divide
  203. → Data at Work: Spencer Westby: Senior Editorial Analyst
  204. CHAPTER 10 • The Chi-Square Test and Measures of Association
  205. The Concept of Chi-Square as a Statistical Test
  206. The Concept of Statistical Independence
  207. The Structure of Hypothesis Testing With Chi-Square
  208. The Assumptions
  209. Stating the Research and the Null Hypotheses
  210. The Concept of Expected Frequencies
  211. Calculating the Expected Frequencies
  212. Calculating the Obtained Chi-Square
  213. The Sampling Distribution of Chi-Square
  214. Determining the Degrees of Freedom
  215. Making a Final Decision
  216. Review
  217. Statistics in Practice: Respondent and Mother Education
  218. → A Closer Look 10.1: A Cautionary Note: Sample Size and Statistical Significance for Chi-Square
  219. Proportional Reduction of Error
  220. → A Closer Look 10.2: What Is Strong? What Is Weak? A Guide to Interpretation
  221. Lambda: A Measure of Association for Nominal Variables
  222. Cramer’s V: A Chi-Square-Related Measure of Association for Nominal Variables
  223. Gamma and Kendall’s Tau-b: Symmetrical Measures of Association for Ordinal Variables
  224. Reading the Research Literature: India’s Internet-Using Population
  225. → Data at Work: Patricio Cumsille: Professor
  226. CHAPTER 11 • Analysis of Variance
  227. Understanding Analysis of Variance
  228. The Structure of Hypothesis Testing With ANOVA
  229. The Assumptions
  230. Stating the Research and the Null Hypotheses and Setting Alpha
  231. The Concepts of Between and Within Total Variance
  232. The F Statistic
  233. → A Closer Look 11.1: Decomposition of SST
  234. Making a Decision
  235. The Five Steps in Hypothesis Testing: A Summary
  236. Statistics in Practice: The Ethical Consumer
  237. → A Closer Look 11.2: Assessing the Relationship Between Variables
  238. Reading the Research Literature: College Satisfaction Among Latino Students
  239. → Data at Work: Kevin Hemminger: Sales Support Manager/ Graduate Program in Research Methods and Statistics
  240. CHAPTER 12 • Regression and Correlation
  241. The Scatter Diagram
  242. Linear Relationships and Prediction Rules
  243. Finding the Best-Fitting Line
  244. → A Closer Look 12.1: Other Regression Techniques
  245. Defining Error
  246. The Residual Sum of Squares (Σe2)
  247. The Least Squares Line
  248. Computing a and b
  249. → A Closer Look 12.2: Understanding the Covariance
  250. Interpreting a and b
  251. A Negative Relationship: Age and Internet Hours per Week
  252. Methods for Assessing the Accuracy of Predictions
  253. Calculating Prediction Errors
  254. Calculating r2
  255. Testing the Significance of r2 Using ANOVA
  256. Making a Decision
  257. Pearson’s Correlation Coefficient (r)
  258. Characteristics of Pearson’s r
  259. Statistics in Practice: Multiple Regression and ANOVA
  260. → A Closer Look 12.3: Spurious Correlations and Confounding Effects
  261. Reading the Research Literature: Academic Intentions and Support
  262. → Data at Work: Shinichi Mizokami: Professor
  263. Appendix A. Table of Random Numbers
  264. Appendix B. The Standard Normal Table
  265. Appendix C. Distribution of t
  266. Appendix D. Distribution of Chi-Square
  267. Appendix E. Distribution of F
  268. Appendix F. A Basic Math Review
  269. Learning Check Solutions
  270. Answers to Odd-Numbered Exercises
  271. Glossary
  272. Notes
  273. Index

 

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