The answers:
1. all individuals of interest
2. individuals actually studied
3. only a sample & might be a bad sample & people might not remember
4. can’t tell
5. most likely not
6. 500
7. 1
8. total area
9. experiment, model, guess
10. no
11. toss it many times
12. unpredictable
13. predictable
14. no
15. no
16. remarkable ones
17. no idea
18. 
19. xp(x)
20. the mean
21. one
22. the variance
23. how far a piece of data is from the mean
24. on average how far the data is from the mean
25. yes
26. the squares of how far the data are from the mean
27. how the data is spread out
28. the center of the data
29.  2
30. 
31. the square root of the average of the squares of how far the data are from the
mean
32. 1
33. 0
34. 1
35. z 
1
2
e

x2
2
36. horizontal distance from the top to where the slope is getting less steep instead of
steeper
37. about 68%
38. about 95%
39. about 99.7%
40. can’t say anything
41. at least 75%
42. at least 88.8%
43. normal
44. 0
45. 1
46. number that describes the population
47. number that describes a sample
48. statistic
_
49. x
50. s
51. s 2
_
52. x
53. s
54. large
55. luck and large sample size
56. luck
57. large sample size
58. 
59.

n
60. not much
61. normal
62. gets closer to normal, Central Limit Theorem
63. A, standard deviation, less
64. highs and lows tend to cancel out
65. standard deviation of all the data in the population, the standard deviation of all
the sample means of a certain sample size, the standard deviation of one sample
66. s and  , the other one is less
67. how many standard deviations from the mean
68. how many games were both wins and at home
69. how many games were at home
70. divide by total
71. F
72. F
73. B has no affect on the chances of A
74. independent
75. P(X)
76. multiple how many choices at each step
77. n!
78. (42)(41)(40)(39)(38)(37)
6! (42)(41)(40)(39)(38)(37)/6!
79. multiplying in a tree diagram & lottery formula
80. 5.5 to 6.5
81. number of failures
82. how many ways you can get k successes in n trials
83. average number of failures
84. anecdotes
85. all the data
86. looking at all the data about child and leukemia and power lines instead of news
interview of one mother with child with leukemia that happens to live near a
power a line
87. a variable that affects the variables you are interested in but is not mentioned
88. child in soccer have higher school scores, but a LV is how much the parents want
their kids to succeed, if they want there kids to succeed a lot then they will be
more likely to put them in soccer and also do things such as to encourage them to
study
89. yes
90. yes
91. no
92. no
93. assume the data are the midpoints of the ranges given
94. the under 25 has a lot more drivers
95. the y-axis does not start at 0 & who decided what the set list of groceries is
96. to understand the data
97. no, definition of child abuse could be different
98. mostly the best students in North Dakota take the SAT while in New Jersey a
much higher percent take the SAT
99. there are many more drivers not drinking so they could easily have more
accidents
100. no
101. Buchanan
102. a higher percent take the SAT in Colorado
103. the Southern states would be towards the bottom
104 the Southern states are mixed in well with the other states
105. r
106. 
107. sum of the squares of the vertical distances from the points to the line
108. nothing
109. different result
110. nothing
111. r uses standardized values
112. 1.43
113. -1 and 1
114. smaller + - 115. no
116. linear
117. exponential & quadratic & logistic
118. yes
119. yes
120. r
121. % of the difference in y explained by the regression line on x
122. yes
123. no
124. no
125. no
126. extrapolation
127. B
128. A
129. no
130. ice cream sales & sunburns
131. lurking variable – how much the parents want their kids to succeed
132. BMI between mothers and daughters, genetic and environmental
133. Gun control laws & violent crime levels
134. yes
135. a gene that both made people addicted to nicotine and gave them lung tumors
136. the gene would have appeared coincidentally later in women(who started
smoking) than men
137. how motivated a person is
138. no
139. yes
140. scatterplot of degree days and gas used to heat a house but half way through the
collection of data solar panels were installed and reduced the gas bills
141. A
142. about right
143. less reliable
144. two-way table
145. a relationship that holds in each subcategory but reverses when all the data is
combined
146. helicopters vs road for accident victims, helicopters do better in serious and less
serious cases, but when combined the road did better
147. observational study
148. experiment
149. experiment
150. heart attacks in menopausal women with hormone replacement therapy
151. no
152. how much the women cared about their health
153. smoking, diet, wealth (wine drinkers tend to smoke less, have a better diet, and
be wealthier affording better health care)
154. experiment
155. get 10 nice roses
no
156. against tuff looking people, in favor of retired people, in favor of teenagers
157. F
158. ignorance & agenda
159. no
160. Ann Landers asking her readers to write in about whether they wish they didn’t
have children
161. bias in favor of their points of view
162. liberal groups ambushed it
163. random
164. rarely
165. no
166. yes
167. survey by phone – people without phones are not covered
168. survey in which not all surveys are completed
169. the people not responding or not covered may be different in important ways
170. no no no in favor of the stadium no
171. yes
172. do you think we are spending too much on “welfare” vs “help for the poor”
173. do you use illegal drugs?
174. have you been to the dentist in the last 6 months?
175. a uniformed police officer asking questions about peoples’ opinion of the police
department
176. has participating in our health program improved your health?
177. teacher A might be easier, students might be better in the online, luck
178. a group that gets the standard treatment
179. divide treatments at random, use a control group, use a lot of subjects
180. rarely would occur by luck
181. dummy treatment that an individual is told is the same as an actual treatment
182. remove the placebo affect, some people respond well to any treatment
183. neither the individuals nor those dealing with them directly know what
treatments are given
184. doctors giving a placebo might not be as positive
185. sample size and difference
186. TV commercials with a captive audience vs how normal people watch TV
187. order of treatments might affect the results
188. helps remove the problem of one group getting better individuals by luck
189. up
190. down
191. up
192. small
193. Ha
194. no
195. 
196. unknown
197. 
198. type I
199. type II
200. 
201. unknown
202. 
203. 
204. type I
205. it is true
206. the sample statistic
Ho is true
207. critical values
208. table
209. test statistic
210. calculation
211. assuming Ho is true it is the chance of finding as strong or stronger evidence
than we got that Ho is not true
212. right stronger true
213. less
214. small
215. no
216. no
217. decide if the lack of meeting conditions is minor or major
218. decide if the problems are minor or major
219. no
220. adults with normal vision, but using students in a psychology class
221. adults, but using students in a sociology class at a college
222. gastric freezing on ulcers
223. the gastric freezing placebo controlled
224. yes
225. remove it
226. no
227. no
228. no
229. no
230. no
231. luck
232. nothing
233. how important it is to get it right, how hard it would be to believe the result,
consequences
234. no
235. go down
236. no
237. no
238. statistically practically
239. no
240. no
241. just by luck a HT will show a result that is not true
242. yes
243. the more times it is repeated the more sure you are
244. 40
8
245.
16
246. normal
247. beer
248. no
249. yes
250. 1
251. z
252. rarely
253. small
254. small differences will be statistically significant
255. Central Limit Theorem
256. round down
257. yes
258. no
259. more
260. 40
8
261.
16
262. t with 15 degrees of freedom
263. a)worse, b)better, c)better
264. Only b, c, d, f, h, i, l, m, and n are probably OK
265. Only c, d, f, h, and k are probably OK
266. shapes
outliers
267. histogram or boxplot
268. histogram or boxplot
269. z
270. subtraction
 Y2
 X2
nX
nY
272. normal
273. 0
nX
271.
 X2

82 9 2

14 12
275. normal
276. 0
274.
82 9 2

14 12
278. p’
279. p
280. p’
281. divide by n
282. n n 2
283. p p
pq
pq
284.
n
n
285. normal
286. 10
277.

 Y2
nY
s X2
sY2
s X2
s2
 Y
n X nY
287. .5 smaller
288. smaller
289. normal
290. .40
(.4)(.6)
291.
200
292. true p’ q’
293. subtraction
px qx
pY qY
294.
nx
nY
295.
296.
px qx
nx
pY qY
nY
p x q x pY qY

nx
nY
p X q X pY qY

nX
nY
p'1 q'1 p' 2 q' 2

n1
n2
p 'pool q 'pool
n1

p 'pool q 'pool
n2
where
p 'pool 
x1  x2
n1  n2
297. 0
(.4)(.6) (.4)(.6)

140
120
299. normal
300. yes
301. yes
302. yes
303. no
304. no
305. 1
306. 1
307.  2 with 24 degrees of freedom
308 division
309. F with 9 degrees of freedom on the top and 7 degrees of freedom on the bottom
310. differ a lot
big
311. Ho is true
312. P(R2 & C3) R2 C3 independent R2 total / grand tot C3 total / grand tot
313. 10
314. normal populations, equal variances, independent samples, SRSs
315. source & luck
316. factor error
317. variance means
318. mean
variances
319. better
320. worse
321. better
322. worse
323. data is linear, normally distributed about the line, independent data, standard
deviation is the same throughout the line
298.
324. yes
325. no
326. easier, less assumptions
327. waste info
328. median Sign Test