Solution Manual for The Practice of Statistics in the Life Sciences, 4th Edition, Brigitte Baldi

This is completed downloadable of Solution Manual for The Practice of Statistics in the Life Sciences, 4th Edition, Brigitte Baldi

 

Product Details:

• 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