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  • ISBN-10 ‏ : ‎ 1319013376
  • ISBN-13 ‏ : ‎ 978-1319013370
  • Author: Brigitte Baldi

See statisics through the eyes of a biologist as Practice of Statistics in the Life Sciences utilizes examples and exercises curated from across the life sciences in order to connect you to the material.

 

Table of Content:

  1. Part I: Collecting and Exploring Data
  2. Chapter 1 Picturing Distributions with Graphs
  3. Individuals and variables
  4. Identifying categorical and quantitative variables
  5. Categorical variables: pie charts and bar graphs
  6. Quantitative variables: histograms
  7. Interpreting histograms
  8. Quantitative variables: dotplots
  9. Time plots
  10. Discussion: (Mis)adventures in data entry
  11. Chapter 1 Summary
  12. This Chapter in Context
  13. Check Your Skills
  14. Chapter 1 Exercises
  15. Chapter 2 Describing Quantitative Distributions with Numbers
  16. Measures of center: median, mean
  17. Measures of spread: percentiles, standard deviation
  18. Graphical displays of numerical summaries
  19. Spotting suspected outliers
  20. Discussion: Dealing with outliers
  21. Organizing a statistical problem
  22. Chapter 2 Summary
  23. This Chapter in Context
  24. Check Your Skills
  25. Chapter 2 Exercises
  26. Chapter 3 Scatterplots and Correlation
  27. Explanatory and response variables
  28. Relationship between two quantitative variables: scatterplots
  29. Adding categorical variables to scatterplots
  30. Measuring linear association: correlation
  31. Chapter 3 Summary
  32. This Chapter in Context
  33. Check Your Skills
  34. Chapter 3 Exercises
  35. Chapter 4 Regression
  36. The least-squares regression line
  37. Facts about least-squares regression
  38. Outliers and influential observations
  39. Working with logarithm transformations
  40. Cautions about correlation and regression
  41. Association does not imply causation
  42. Chapter 4 Summary
  43. This Chapter in Context
  44. Check Your Skills
  45. Chapter 4 Exercises
  46. Chapter 5 Two-Way Tables
  47. Marginal distributions
  48. Conditional distributions
  49. Simpson’s paradox
  50. Chapter 5 Summary
  51. This Chapter in Context
  52. Check Your Skills
  53. Chapter 5 Exercises
  54. Chapter 6 Samples and Observational Studies
  55. Observation versus experiment
  56. Sampling
  57. Sampling designs
  58. Sample surveys
  59. Cohorts and case-control studies
  60. Chapter 6 Summary
  61. This Chapter in Context
  62. Check Your Skills
  63. Chapter 6 Exercises
  64. Chapter 7 Designing Experiments
  65. Designing experiments
  66. Randomized comparative experiments
  67. Common experimental designs
  68. Cautions about experimentation
  69. Ethics in experimentation
  70. Discussion: The Tuskegee syphilis study
  71. Chapter 7 Summary
  72. This Chapter in Context
  73. Check Your Skills
  74. Chapter 7 Exercises
  75. Chapter 8 Collecting and Exploring Data: Part I Review
  76. Part I summary
  77. Comprehensive review exercises
  78. Large data set exercises
  79. Online data sources
  80. EESEE case studies
  81. Part II: From Chance to Inference
  82. Chapter 9 Essential Probability Rules
  83. The idea of probability
  84. Probability models
  85. Probability rules
  86. Discrete versus continuous probability models
  87. Random variables
  88. Risk and odds
  89. Chapter 9 Summary
  90. This Chapter in Context
  91. Check Your Skills
  92. Chapter 9 Exercises
  93. Chapter 10 Independence and Conditional Probabilities
  94. Relationships among several events
  95. Conditional probability
  96. General probability rules
  97. Tree diagrams
  98. Bayes’s theorem
  99. Discussion: Making sense of conditional probabilities in diagnostic tests
  100. Chapter 10 Summary
  101. This Chapter in Context
  102. Check Your Skills
  103. Chapter 10 Exercises
  104. Chapter 11 The Normal Distributions
  105. Normal distributions
  106. The 68–95–99.7 rule
  107. The standard Normal distribution
  108. Finding Normal probabilities
  109. Finding percentiles
  110. Using the standard Normal table
  111. Normal quantile plots
  112. Chapter 11 Summary
  113. This Chapter in Context
  114. Check Your Skills
  115. Chapter 11 Exercises
  116. Chapter 12 Discrete Probability Distributions
  117. The binomial setting and binomial distributions
  118. Binomial probabilities
  119. Binomial mean and standard deviation
  120. The Normal approximation to binomial distributions
  121. The Poisson distributions
  122. Poisson probabilities
  123. Chapter 12 Summary
  124. This Chapter in Context
  125. Check Your Skills
  126. Chapter 12 Exercises
  127. Chapter 13 Sampling Distributions
  128. Parameters and statistics
  129. Statistical estimation and sampling distributions
  130. The sampling distribution of x̄
  131. The central limit theorem
  132. The sampling distribution of p̂
  133. The law of large numbers
  134. Chapter 13 Summary
  135. This Chapter in Context
  136. Check Your Skills
  137. Chapter 13 Exercises
  138. Chapter 14 Introduction to Inference
  139. Statistical estimation
  140. Margin of error and confidence level
  141. Confidence intervals for the mean μ
  142. Hypothesis testing
  143. P-value and statistical significance
  144. Tests for a population mean
  145. Tests from confidence intervals
  146. Chapter 14 Summary
  147. This Chapter in Context
  148. Check Your Skills
  149. Chapter 14 Exercises
  150. Chapter 15 Inference in Practice
  151. Conditions for inference in practice
  152. How confidence intervals behave
  153. How hypothesis tests behave
  154. Discussion: The scientific approach
  155. Planning studies: selecting an appropriate sample size
  156. Chapter 15 Summary
  157. This Chapter in Context
  158. Check Your Skills
  159. Chapter 15 Exercises
  160. Chapter 16 From Chance to Inference: Part II Review
  161. Part II summary
  162. Comprehensive review exercises
  163. Advanced topics (optional material)
  164. Online data sources
  165. EESEE case studies
  166. Part III: Statistical Inference
  167. Chapter 17 Inference about a Population Mean
  168. Conditions for inference
  169. The t distributions
  170. The one-sample t confidence interval
  171. The one-sample t test
  172. Matched pairs t procedures
  173. Robustness of t procedures
  174. Chapter 17 Summary
  175. This Chapter in Context
  176. Check Your Skills
  177. Chapter 17 Exercises
  178. Chapter 18 Comparing Two Means
  179. Comparing two population means
  180. Two-sample t procedures
  181. Robustness again
  182. Avoid the pooled two-sample t procedures
  183. Avoid inference about standard deviations
  184. Chapter 18 Summary
  185. This Chapter in Context
  186. Check Your Skills
  187. Chapter 18 Exercises
  188. Chapter 19 Inference about a Population Proportion
  189. The sample proportion p̂
  190. Large-sample confidence intervals for a proportion
  191. Accurate confidence intervals for a proportion
  192. Choosing the sample size
  193. Hypothesis tests for a proportion
  194. Chapter 19 Summary
  195. This Chapter in Context
  196. Check Your Skills
  197. Chapter 19 Exercises
  198. Chapter 20 Comparing Two Proportions
  199. Two-sample problems: proportions
  200. The sampling distribution of a difference between proportions
  201. Large-sample confidence intervals for comparing proportions
  202. Accurate confidence intervals for comparing proportions
  203. Hypothesis tests for comparing proportions
  204. Relative risk and odds ratio
  205. Discussion: Assessing and understanding health risks
  206. Chapter 20 Summary
  207. This Chapter in Context
  208. Check Your Skills
  209. Chapter 20 Exercises
  210. Chapter 21 The Chi-Square Test for Goodness of Fit
  211. Hypotheses for goodness of fit
  212. Expected counts and chi-square statistic
  213. The chi-square test for goodness of fit
  214. Interpreting significant chi-square results
  215. Conditions for the chi-square test
  216. Chapter 21 Summary
  217. This Chapter in Context
  218. Check Your Skills
  219. Chapter 21 Exercises
  220. Chapter 22 The Chi-Square Test for Two-Way Tables
  221. Two-way tables
  222. Hypotheses for two-way tables of counts
  223. Expected counts and chi-square statistic
  224. The chi-square test
  225. Conditions for the chi-square test
  226. The chi-square test and the two-sample z test
  227. Chapter 22 Summary
  228. This Chapter in Context
  229. Check Your Skills
  230. Chapter 22 Exercises
  231. Chapter 23 Inference for Regression
  232. The regression parameters
  233. Testing the hypothesis of no linear relationship
  234. Testing lack of correlation
  235. Confidence intervals for the regression slope
  236. Inference about prediction
  237. Checking the conditions for inference
  238. Chapter 23 Summary
  239. This Chapter in Context
  240. Check Your Skills
  241. Chapter 23 Exercises
  242. Chapter 24 One-Way Analysis of Variance: Comparing Several Means
  243. Comparing several means
  244. The F statistic
  245. The analysis of variance F test
  246. Conditions for ANOVA
  247. Details of ANOVA calculations
  248. Chapter 24 Summary
  249. This Chapter in Context
  250. Check Your Skills
  251. Chapter 24 Exercises
  252. Chapter 25 Statistical Inference: Part III Review
  253. Essential concepts from Parts I and II
  254. Part III summary
  255. Comprehensive review exercises: inference selection
  256. Comprehensive review exercises: analysis and conclusion
  257. Large data set exercises
  258. Online data sources
  259. EESEE case studies
  260. Part IV Optional Companion Chapters (available on the PSLS 4e Companion Website)
  261. Chapter 26 More about Analysis of Variance: Follow-up Tests and Two-Way ANOVA
  262. Beyond one-way ANOVA
  263. Follow-up analysis: Tukey pairwise multiple comparisons
  264. Follow-up analysis: contrasts
  265. Two-way ANOVA: conditions, main effects, and interaction
  266. Inference for two-way ANOVA
  267. Some details of two-way ANOVA
  268. Chapter 26 Summary
  269. Statistics in Summary
  270. This Chapter in Context
  271. Check Your Skills
  272. Chapter 26 Exercises
  273. Chapter 27 Nonparametric Tests
  274. Comparing two samples: the Wilcoxon rank sum test
  275. Matched pairs: the Wilcoxon signed rank test
  276. Comparing several samples: the Kruskal-Wallis test
  277. Chapter 27 Summary
  278. Statistics in Summary
  279. This Chapter in Context
  280. Check Your Skills
  281. Chapter 27 Exercises
  282. Chapter 28 Multiple and Logistic Regression
  283. Parallel regression lines
  284. Estimating parameters
  285. Using technology
  286. Conditions for inference
  287. Inference for multiple regression
  288. Interaction
  289. A case study for multiple regression
  290. Logistic regression
  291. Inference for logistic regression
  292. Chapter 28 Summary
  293. Statistics in Summary
  294. This Chapter in Context
  295. Check Your Skills
  296. Chapter 28 Exercises
  297. Back Matter
  298. Notes and Data Sources
  299. Notes
  300. Tables
  301. TABLE A: Random Digits
  302. TABLE B: Standard Normal Probabilities
  303. TABLE C: t Distribution Critical Values
  304. TABLE D: Chi-square Distribution Critical Values
  305. TABLE E: Critical Values of the Correlation r
  306. TABLE F: F Distribution Critical Values
  307. TABLE G: Critical values m* for Tukey pairwise multiple comparisons with 95% confidence level, k comparisons, and N – k degrees of freedom (df)
  308. Answers to Selected Exercises
  309. Some Studies Recurring Across Chapters
  310. Index
  311. A
  312. B
  313. C
  314. D
  315. E
  316. F
  317. G
  318. H
  319. I
  320. L
  321. M
  322. N
  323. O
  324. P
  325. Q
  326. R
  327. S
  328. T
  329. U
  330. V
  331. W
  332. X
  333. Z
  334. Symbols
  335. Back Cover

 

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