# Case Study 13.2.1: Acrophobia # The data: Block Treatment ScoreDiff 1 A CD 8 2 A DP 2 3 A LM -2 4 B CD 11 5 B DP 1 6 B LM 0 7 C CD 9 8 C DP 12 9 C LM 6 10 D CD 16 11 D DP 11 12 D LM 2 13 E CD 24 14 E DP 19 15 E LM 11 # Select and copy the data, the in R: case13.2.1.df <- read.table(file='clipboard',header=T) # Then replicate results in text via: attach(case13.2.1.df) cs13.2.1.aov <- aov(ScoreDiff ~ Block + Treatment) summary(cs13.2.1.aov) # Exercise 13.2.2 (and 13.2.7) City Network Share A ABC 19.7 A CBS 16.1 A NBC 18.2 B ABC 18.6 B CBS 15.8 B NBC 17.9 C ABC 19.1 C CBS 14.6 C NBC 15.3 D ABC 17.9 D CBS 17.1 D NBC 18.0 # Basic descriptive statistics: par(mfrow=c(2,2)) boxplot(split(Share,Network)) tapply(Share,Network,mean) interaction.plot(Network, City, Share) # RCBD ANOVA: temp.aov <- aov(Share ~ Network + City) summary(temp.aov)
EXAM DATA
# National Universities
Row Tier Name Private GradRate SAT
1 1 UniversityOfWashington 0 75 1190
2 1 UniversityOfTexasAustin 0 77 1245
3 1 CollegeOfWilliamAndMary 0 92 1340
4 1 WakeForestUniversity 1 88 1320
5 2 UniversityOfDelaware 0 76 1200
6 2 BrighamYoungUniversity 1 71 1245
7 2 UniversityOfArizona 0 59 1110
8 2 BaylorUniversity 1 74 1205
9 2 ArizonaStateUniversity 0 56 1095
10 2 ClarksonUniversity 1 74 1185
11 4 OaklandUniversity 0 45 1010
12 4 LouisianaTechUniversity 0 49 1050
13 3 SetonHallUniversity 1 58 1085
14 4 UnivOfSouthernMississippi 0 46 1030
15 3 UnivOfMissouriKansasCity 0 45 1085
16 4 EastCarolinaUniversity 0 56 998
17 3 UniversityOfIdaho 0 55 1070
18 3 DePaulUniversity 1 64 1090
19 4 UnivOfTexasArlington 0 42 1075
20 3 PaceUniversity 1 56 1070
# Horton
female phsxabus indtot Group
1 0 1 39 MaleYes
2 0 1 43 MaleYes
3 0 1 41 MaleYes
4 1 1 28 FemaleYes
5 0 0 38 MaleNo
6 1 0 29 FemaleNo
7 1 1 38 FemaleYes
8 0 1 44 MaleYes
9 1 1 44 FemaleYes
10 0 1 44 MaleYes
11 1 1 11 FemaleYes
12 0 1 45 MaleYes
13 0 0 40 MaleNo
14 0 1 41 MaleYes
15 0 0 38 MaleNo
16 1 1 26 FemaleYes
17 0 0 17 MaleNo
18 0 1 40 MaleYes
19 1 1 37 FemaleYes
20 0 1 37 MaleYes
21 0 0 36 MaleNo
22 0 1 27 MaleYes
23 0 1 42 MaleYes
24 0 0 42 MaleNo
25 0 1 45 MaleYes
26 1 1 40 FemaleYes
27 0 1 34 MaleYes
28 0 1 42 MaleYes
29 0 0 37 MaleNo
30 0 1 41 MaleYes
31 0 1 37 MaleYes
32 0 1 44 MaleYes
33 0 1 41 MaleYes
34 0 1 35 MaleYes
35 0 0 21 MaleNo
36 0 0 30 MaleNo
37 0 0 33 MaleNo
38 0 1 43 MaleYes
39 0 1 41 MaleYes
40 1 1 36 FemaleYes
41 0 1 41 MaleYes
42 0 0 32 MaleNo
43 0 1 41 MaleYes
44 0 1 39 MaleYes
45 0 0 22 MaleNo
46 0 1 39 MaleYes
47 0 1 43 MaleYes
48 0 1 38 MaleYes
49 1 0 8 FemaleNo
50 0 0 36 MaleNo
51 0 1 42 MaleYes
52 0 0 31 MaleNo
53 0 1 44 MaleYes
54 1 1 31 FemaleYes
55 0 1 40 MaleYes
56 1 1 32 FemaleYes
57 0 0 29 MaleNo
58 0 1 44 MaleYes
59 0 0 43 MaleNo
60 0 1 38 MaleYes
61 0 1 34 MaleYes
62 0 1 41 MaleYes
63 0 1 41 MaleYes
64 1 1 20 FemaleYes
65 1 0 29 FemaleNo
66 0 1 38 MaleYes
67 0 1 42 MaleYes
68 0 1 41 MaleYes
69 0 1 38 MaleYes
70 1 1 43 FemaleYes
71 0 0 38 MaleNo
72 0 1 44 MaleYes
73 1 1 37 FemaleYes
74 1 1 40 FemaleYes
75 0 1 38 MaleYes
76 0 1 29 MaleYes
77 0 1 35 MaleYes
78 0 1 28 MaleYes
79 0 1 40 MaleYes
80 0 1 44 MaleYes
81 0 0 36 MaleNo
82 0 0 29 MaleNo
83 0 1 42 MaleYes
84 0 1 40 MaleYes
85 0 0 29 MaleNo
86 1 1 40 FemaleYes
87 0 1 39 MaleYes
88 0 1 39 MaleYes
89 0 0 35 MaleNo
90 0 0 38 MaleNo
91 0 1 40 MaleYes
92 0 1 44 MaleYes
93 0 0 19 MaleNo
94 0 0 43 MaleNo
95 1 1 44 FemaleYes
96 0 1 34 MaleYes
97 0 0 42 MaleNo
98 1 1 42 FemaleYes
99 0 1 40 MaleYes
100 0 1 39 MaleYes
101 0 0 40 MaleNo
102 1 1 33 FemaleYes
103 0 1 38 MaleYes
104 0 1 41 MaleYes
105 0 1 42 MaleYes
106 0 0 37 MaleNo
107 0 1 43 MaleYes
108 0 1 38 MaleYes
109 0 0 33 MaleNo
110 0 1 34 MaleYes
111 0 1 28 MaleYes
112 1 0 19 FemaleNo
113 0 0 43 MaleNo
114 1 1 33 FemaleYes
115 1 1 31 FemaleYes
116 0 1 42 MaleYes
117 0 1 33 MaleYes
118 0 0 36 MaleNo
119 1 1 43 FemaleYes
120 0 0 19 MaleNo
121 1 1 37 FemaleYes
122 0 1 25 MaleYes
123 0 1 42 MaleYes
124 0 0 31 MaleNo
125 1 0 25 FemaleNo
126 0 1 39 MaleYes
127 0 1 41 MaleYes
128 1 1 28 FemaleYes
129 0 1 40 MaleYes
130 0 0 40 MaleNo
131 0 0 29 MaleNo
132 1 1 39 FemaleYes
133 1 1 21 FemaleYes
134 0 1 39 MaleYes
135 1 1 39 FemaleYes
136 0 0 38 MaleNo
137 1 1 36 FemaleYes
138 0 1 42 MaleYes
139 0 1 36 MaleYes
140 0 1 36 MaleYes
141 0 1 41 MaleYes
142 0 1 42 MaleYes
143 0 1 37 MaleYes
144 1 1 33 FemaleYes
145 0 1 42 MaleYes
146 0 1 37 MaleYes
147 1 0 25 FemaleNo
148 0 1 43 MaleYes
149 1 1 35 FemaleYes
150 0 0 40 MaleNo
151 1 1 35 FemaleYes
152 0 1 33 MaleYes
153 0 0 43 MaleNo
154 0 1 43 MaleYes
155 1 1 25 FemaleYes
156 0 1 30 MaleYes
157 0 1 44 MaleYes
158 0 1 35 MaleYes
159 1 1 38 FemaleYes
160 0 0 37 MaleNo
161 0 1 29 MaleYes
162 0 1 43 MaleYes
163 0 1 30 MaleYes
164 1 1 38 FemaleYes
165 0 1 37 MaleYes
166 0 1 29 MaleYes
167 0 1 41 MaleYes
168 0 1 37 MaleYes
169 0 1 44 MaleYes
170 0 1 35 MaleYes
171 0 1 41 MaleYes
172 1 0 31 FemaleNo
173 0 0 42 MaleNo
174 1 1 36 FemaleYes
175 0 1 38 MaleYes
176 0 1 41 MaleYes
177 0 1 43 MaleYes
178 0 0 40 MaleNo
179 0 0 36 MaleNo
180 1 1 39 FemaleYes
181 1 1 38 FemaleYes
182 0 0 42 MaleNo
183 0 1 34 MaleYes
184 1 1 35 FemaleYes
185 0 0 34 MaleNo
186 1 1 44 FemaleYes
187 1 1 41 FemaleYes
188 0 1 41 MaleYes
189 0 1 35 MaleYes
190 0 0 36 MaleNo
191 0 1 36 MaleYes
192 1 1 39 FemaleYes
193 0 1 44 MaleYes
194 0 1 41 MaleYes
195 1 1 37 FemaleYes
196 1 1 32 FemaleYes
197 0 1 36 MaleYes
198 0 0 32 MaleNo
199 0 1 34 MaleYes
200 0 0 38 MaleNo
201 0 1 39 MaleYes
202 0 0 29 MaleNo
203 0 1 41 MaleYes
204 0 0 37 MaleNo
205 1 1 32 FemaleYes
206 0 1 43 MaleYes
207 0 0 42 MaleNo
208 0 0 33 MaleNo
209 0 1 28 MaleYes
210 0 1 43 MaleYes
211 1 1 40 FemaleYes
212 1 1 23 FemaleYes
213 1 1 33 FemaleYes
214 0 1 38 MaleYes
215 0 1 40 MaleYes
216 1 1 21 FemaleYes
217 0 1 36 MaleYes
218 1 1 32 FemaleYes
219 0 1 32 MaleYes
220 1 1 43 FemaleYes
221 1 1 31 FemaleYes
222 0 0 41 MaleNo
223 0 1 32 MaleYes
224 0 1 40 MaleYes
225 0 1 40 MaleYes
226 0 1 41 MaleYes
227 0 0 42 MaleNo
228 1 1 34 FemaleYes
229 1 1 28 FemaleYes
230 0 0 29 MaleNo
231 0 1 40 MaleYes
232 0 1 34 MaleYes
233 1 1 34 FemaleYes
234 1 1 36 FemaleYes
235 0 1 43 MaleYes
236 0 0 36 MaleNo
237 0 0 35 MaleNo
238 0 1 35 MaleYes
239 1 1 34 FemaleYes
240 0 1 42 MaleYes
241 1 1 33 FemaleYes
242 0 1 34 MaleYes
243 0 1 19 MaleYes
244 0 0 33 MaleNo
245 0 0 30 MaleNo
246 1 1 20 FemaleYes
247 1 0 26 FemaleNo
248 0 0 39 MaleNo
249 0 0 45 MaleNo
250 0 1 43 MaleYes
251 0 1 36 MaleYes
252 0 1 37 MaleYes
253 0 1 42 MaleYes
254 0 1 44 MaleYes
255 0 1 40 MaleYes
256 1 1 41 FemaleYes
257 0 1 33 MaleYes
258 0 1 44 MaleYes
259 0 1 33 MaleYes
260 0 1 42 MaleYes
261 1 1 27 FemaleYes
262 0 1 33 MaleYes
263 0 1 38 MaleYes
264 1 1 38 FemaleYes
265 0 1 45 MaleYes
266 0 1 40 MaleYes
267 1 1 23 FemaleYes
268 0 1 42 MaleYes
269 0 1 39 MaleYes
270 0 1 21 MaleYes
271 0 1 37 MaleYes
272 0 1 4 MaleYes
273 0 1 38 MaleYes
274 0 1 31 MaleYes
275 0 1 36 MaleYes
276 1 1 38 FemaleYes
277 0 0 42 MaleNo
278 0 1 28 MaleYes
279 0 1 44 MaleYes
280 0 1 38 MaleYes
281 0 1 42 MaleYes
282 0 0 28 MaleNo
283 0 1 40 MaleYes
284 0 1 44 MaleYes
285 0 1 37 MaleYes
286 0 0 32 MaleNo
287 0 1 30 MaleYes
288 0 1 39 MaleYes
289 0 1 41 MaleYes
290 0 0 31 MaleNo
291 0 1 39 MaleYes
292 0 1 40 MaleYes
293 0 1 41 MaleYes
294 0 1 32 MaleYes
295 1 0 20 FemaleNo
296 1 1 28 FemaleYes
297 0 1 38 MaleYes
298 1 1 25 FemaleYes
299 0 0 39 MaleNo
300 1 0 33 FemaleNo
301 0 0 40 MaleNo
302 0 1 39 MaleYes
303 0 1 38 MaleYes
304 0 0 36 MaleNo
305 1 1 33 FemaleYes
306 0 0 29 MaleNo
307 0 0 27 MaleNo
308 1 1 36 FemaleYes
309 0 0 29 MaleNo
310 0 1 39 MaleYes
311 0 1 40 MaleYes
312 1 1 22 FemaleYes
313 0 0 29 MaleNo
314 0 0 32 MaleNo
315 0 0 38 MaleNo
316 1 1 27 FemaleYes
317 1 1 32 FemaleYes
318 0 1 37 MaleYes
319 1 1 32 FemaleYes
320 0 0 31 MaleNo
321 0 0 19 MaleNo
322 0 1 42 MaleYes
323 0 1 41 MaleYes
324 0 0 34 MaleNo
325 1 1 40 FemaleYes
326 0 1 40 MaleYes
327 0 0 37 MaleNo
328 0 1 39 MaleYes
329 0 1 26 MaleYes
330 0 1 37 MaleYes
331 1 1 36 FemaleYes
332 0 1 43 MaleYes
333 0 1 32 MaleYes
334 1 0 40 FemaleNo
335 0 1 42 MaleYes
336 1 0 28 FemaleNo
337 0 1 43 MaleYes
338 0 1 12 MaleYes
339 0 1 44 MaleYes
340 1 1 27 FemaleYes
341 0 0 40 MaleNo
342 1 1 41 FemaleYes
343 0 1 41 MaleYes
344 0 1 38 MaleYes
345 1 0 22 FemaleNo
346 0 1 41 MaleYes
347 0 0 37 MaleNo
348 0 1 40 MaleYes
349 0 0 41 MaleNo
350 0 1 41 MaleYes
351 0 1 31 MaleYes
352 0 1 43 MaleYes
353 0 1 39 MaleYes
354 1 0 15 FemaleNo
355 0 1 40 MaleYes
356 0 1 24 MaleYes
357 1 1 35 FemaleYes
358 0 1 42 MaleYes
359 0 0 29 MaleNo
360 1 1 32 FemaleYes
361 0 1 31 MaleYes
362 1 0 44 FemaleNo
363 0 0 38 MaleNo
364 1 1 40 FemaleYes
365 0 1 42 MaleYes
366 0 0 35 MaleNo
367 0 1 37 MaleYes
368 1 0 13 FemaleNo
369 0 1 43 MaleYes
370 0 1 40 MaleYes
371 0 1 33 MaleYes
372 0 1 37 MaleYes
373 0 1 36 MaleYes
374 0 1 26 MaleYes
375 0 0 42 MaleNo
376 0 1 35 MaleYes
377 0 0 41 MaleNo
378 0 1 41 MaleYes
379 1 1 34 FemaleYes
380 0 0 36 MaleNo
381 0 1 14 MaleYes
382 0 1 42 MaleYes
383 0 1 33 MaleYes
384 0 1 10 MaleYes
385 0 1 32 MaleYes
386 0 1 39 MaleYes
387 0 1 38 MaleYes
388 0 0 41 MaleNo
389 0 1 36 MaleYes
390 1 1 38 FemaleYes
391 1 1 41 FemaleYes
392 0 1 39 MaleYes
393 0 1 41 MaleYes
394 0 0 39 MaleNo
395 0 1 25 MaleYes
396 0 1 32 MaleYes
397 0 0 39 MaleNo
398 0 1 43 MaleYes
399 0 0 31 MaleNo
400 0 1 31 MaleYes
401 0 0 40 MaleNo
402 0 1 43 MaleYes
403 0 1 29 MaleYes
404 0 0 41 MaleNo
405 0 1 43 MaleYes
406 0 0 9 MaleNo
407 0 0 39 MaleNo
408 0 0 37 MaleNo
409 1 1 37 FemaleYes
410 0 0 40 MaleNo
411 0 0 31 MaleNo
412 0 1 42 MaleYes
413 0 1 42 MaleYes
414 1 0 37 FemaleNo
415 0 0 15 MaleNo
416 0 0 37 MaleNo
417 1 0 13 FemaleNo
418 0 1 35 MaleYes
419 0 0 30 MaleNo
420 0 1 34 MaleYes
421 0 0 44 MaleNo
422 0 0 32 MaleNo
423 0 1 32 MaleYes
424 0 1 38 MaleYes
425 0 1 30 MaleYes
426 0 0 34 MaleNo
427 0 1 44 MaleYes
428 1 0 37 FemaleNo
429 0 1 40 MaleYes
430 0 1 41 MaleYes
431 1 1 44 FemaleYes
432 0 0 30 MaleNo
433 0 0 42 MaleNo
434 0 1 36 MaleYes
435 1 1 41 FemaleYes
436 0 1 45 MaleYes
437 0 1 36 MaleYes
438 0 0 38 MaleNo
439 0 0 39 MaleNo
440 0 1 44 MaleYes
441 0 1 28 MaleYes
442 0 1 32 MaleYes
443 1 0 28 FemaleNo
444 1 1 34 FemaleYes
445 0 0 26 MaleNo
446 0 1 43 MaleYes
447 1 1 35 FemaleYes
448 1 0 6 FemaleNo
449 0 0 31 MaleNo
450 0 1 42 MaleYes
451 0 1 35 MaleYes
452 1 1 33 FemaleYes
# R Code for Question 3
reps <- 100
results <- numeric(reps)
for (i in 1:reps) {
success <- 0
sum <- 0
K <- 0
while (success==0) {
sum <- sum + runif(1)
success <- success + (sum>1)
K <- K + 1
}
results[i] <- K
}
# Stools
Type Subject Effort
1 A a 12
2 A b 10
3 A c 7
4 A d 7
5 A e 8
6 A f 9
7 A g 8
8 A h 7
9 A i 9
10 B a 15
11 B b 14
12 B c 14
13 B d 11
14 B e 11
15 B f 11
16 B g 12
17 B h 11
18 B i 13
19 C a 12
20 C b 13
21 C c 13
22 C d 10
23 C e 8
24 C f 11
25 C g 12
26 C h 8
27 C i 10
28 D a 10
29 D b 12
30 D c 9
31 D d 9
32 D e 7
33 D f 10
34 D g 11
35 D h 7
36 D i 8