Now develop a regression model to predict number of Personnel by number of Beds. In comparison to the previous model, which model Personnel? Why? Model 1: Predicting personnel by the number of births Model 2: Predicting personnel by the number of beds O Model 1 because the coefficient of determination is higher. Model 1 because the coefficient of determination is lower.
Now develop a regression model to predict number of Personnel by number of Beds. In comparison to the previous model, which model Personnel? Why? Model 1: Predicting personnel by the number of births Model 2: Predicting personnel by the number of beds O Model 1 because the coefficient of determination is higher. Model 1 because the coefficient of determination is lower.
College Algebra
7th Edition
ISBN:9781305115545
Author:James Stewart, Lothar Redlin, Saleem Watson
Publisher:James Stewart, Lothar Redlin, Saleem Watson
Chapter1: Equations And Graphs
Section: Chapter Questions
Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...
Related questions
Question
Hospital | Births | Personnel | Beds |
1 | 312 | 792 | 210 |
2 | 1077 | 1762 | 347 |
3 | 1027 | 2310 | 511 |
4 | 355 | 328 | 142 |
5 | 168 | 181 | 40 |
6 | 3810 | 1077 | 220 |
7 | 735 | 742 | 137 |
8 | 1 | 131 | 80 |
9 | 1733 | 1594 | 440 |
10 | 257 | 233 | 48 |
11 | 169 | 241 | 56 |
12 | 430 | 203 | 46 |
13 | 0 | 325 | 109 |
14 | 2049 | 676 | 306 |
15 | 211 | 347 | 7 |
16 | 16 | 79 | 16 |
17 | 2648 | 505 | 167 |
18 | 2450 | 1543 | 444 |
19 | 1465 | 755 | 236 |
20 | 0 | 959 | 247 |
21 | 1993 | 325 | 93 |
22 | 2275 | 954 | 236 |
23 | 1494 | 1091 | 220 |
24 | 1313 | 671 | 228 |
25 | 451 | 300 | 83 |
26 | 1689 | 753 | 273 |
27 | 1583 | 607 | 225 |
28 | 2017 | 929 | 236 |
29 | 995 | 354 | 80 |
30 | 2045 | 408 | 78 |
31 | 1686 | 1251 | 197 |
32 | 503 | 386 | 60 |
33 | 126 | 144 | 31 |
34 | 2026 | 2047 | 264 |
35 | 1412 | 1343 | 246 |
36 | 1517 | 1723 | 556 |
37 | 0 | 96 | 56 |
38 | 0 | 529 | 120 |
39 | 2719 | 3694 | 674 |
40 | 1074 | 1042 | 414 |
41 | 1421 | 1071 | 320 |
42 | 762 | 1525 | 315 |
43 | 3194 | 1983 | 344 |
44 | 496 | 670 | 168 |
45 | 1442 | 1653 | 315 |
46 | 0 | 167 | 88 |
47 | 1107 | 793 | 245 |
48 | 2989 | 841 | 311 |
49 | 113 | 316 | 233 |
50 | 0 | 93 | 46 |
51 | 0 | 373 | 103 |
52 | 173 | 263 | 331 |
53 | 1064 | 943 | 186 |
54 | 759 | 605 | 177 |
55 | 1317 | 596 | 149 |
56 | 1751 | 1165 | 286 |
57 | 0 | 568 | 488 |
58 | 0 | 507 | 242 |
59 | 714 | 479 | 128 |
60 | 99 | 136 | 33 |
61 | 2243 | 1456 | 255 |
62 | 3966 | 3486 | 481 |
63 | 1308 | 885 | 191 |
64 | 0 | 243 | 60 |
65 | 2514 | 1001 | 155 |
66 | 3714 | 3301 | 626 |
67 | 126 | 337 | 105 |
68 | 556 | 1193 | 59 |
69 | 1327 | 1161 | 258 |
70 | 415 | 322 | 47 |
71 | 216 | 185 | 22 |
72 | 339 | 205 | 53 |
73 | 1217 | 1224 | 244 |
74 | 2641 | 1704 | 352 |
75 | 790 | 815 | 366 |
76 | 520 | 712 | 194 |
77 | 35 | 156 | 109 |
78 | 1168 | 1769 | 285 |
79 | 793 | 875 | 175 |
80 | 0 | 790 | 342 |
81 | 0 | 308 | 140 |
82 | 14 | 70 | 50 |
83 | 0 | 494 | 214 |
84 | 0 | 111 | 80 |
85 | 0 | 1618 | 467 |
86 | 0 | 244 | 80 |
87 | 776 | 525 | 160 |
88 | 451 | 472 | 106 |
89 | 0 | 94 | 40 |
90 | 145 | 297 | 99 |
91 | 1284 | 847 | 133 |
92 | 1 | 234 | 138 |
93 | 319 | 401 | 88 |
94 | 2154 | 3928 | 573 |
95 | 295 | 198 | 44 |
96 | 496 | 1231 | 225 |
97 | 589 | 545 | 105 |
98 | 806 | 663 | 100 |
99 | 701 | 820 | 186 |
100 | 3968 | 2581 | 375 |
101 | 0 | 1298 | 485 |
102 | 0 | 126 | 64 |
103 | 3655 | 2534 | 495 |
104 | 0 | 251 | 114 |
105 | 0 | 85 | 62 |
106 | 0 | 432 | 149 |
107 | 0 | 864 | 427 |
108 | 0 | 66 | 40 |
109 | 3063 | 556 | 129 |
110 | 169 | 347 | 149 |
111 | 66 | 239 | 71 |
112 | 827 | 973 | 256 |
113 | 570 | 439 | 153 |
114 | 0 | 1849 | 1297 |
115 | 0 | 102 | 70 |
116 | 0 | 262 | 69 |
117 | 342 | 885 | 71 |
118 | 494 | 549 | 243 |
119 | 0 | 611 | 206 |
120 | 0 | 330 | 62 |
121 | 0 | 1471 | 219 |
122 | 0 | 75 | 54 |
123 | 286 | 262 | 24 |
124 | 235 | 328 | 151 |
125 | 339 | 377 | 160 |
126 | 398 | 575 | 262 |
127 | 1275 | 1916 | 296 |
128 | 5699 | 2620 | 671 |
129 | 1364 | 571 | 184 |
130 | 714 | 703 | 249 |
131 | 0 | 535 | 157 |
132 | 0 | 160 | 100 |
133 | 0 | 202 | 100 |
134 | 779 | 1330 | 375 |
135 | 0 | 370 | 123 |
136 | 2202 | 3123 | 457 |
137 | 3346 | 2745 | 263 |
138 | 1071 | 815 | 160 |
139 | 352 | 576 | 69 |
140 | 254 | 502 | 153 |
141 | 0 | 808 | 260 |
142 | 0 | 50 | 34 |
143 | 699 | 728 | 479 |
144 | 2462 | 4087 | 973 |
145 | 3311 | 3012 | 440 |
146 | 0 | 68 | 51 |
147 | 4207 | 3090 | 347 |
148 | 0 | 1358 | 612 |
149 | 339 | 576 | 141 |
150 | 130 | 284 | 115 |
151 | 91 | 145 | 50 |
152 | 1143 | 2312 | 261 |
153 | 0 | 1124 | 334 |
154 | 0 | 336 | 228 |
155 | 509 | 415 | 85 |
156 | 1026 | 1779 | 357 |
157 | 0 | 338 | 189 |
158 | 447 | 453 | 139 |
159 | 1161 | 437 | 60 |
160 | 0 | 261 | 164 |
161 | 922 | 609 | 105 |
162 | 562 | 647 | 114 |
163 | 78 | 61 | 73 |
164 | 0 | 2074 | 314 |
165 | 2122 | 2232 | 350 |
166 | 0 | 948 | 602 |
167 | 0 | 409 | 74 |
168 | 0 | 153 | 53 |
169 | 710 | 741 | 152 |
170 | 1165 | 1625 | 317 |
171 | 466 | 538 | 43 |
172 | 1106 | 789 | 269 |
173 | 376 | 395 | 79 |
174 | 0 | 956 | 181 |
175 | 637 | 362 | 122 |
176 | 0 | 144 | 65 |
177 | 352 | 229 | 97 |
178 | 447 | 396 | 169 |
179 | 1227 | 2256 | 407 |
180 | 963 | 731 | 160 |
181 | 3038 | 1477 | 117 |
182 | 0 | 102 | 80 |
183 | 0 | 106 | 100 |
184 | 868 | 939 | 370 |
185 | 1189 | 392 | 123 |
186 | 2849 | 3516 | 380 |
187 | 1728 | 785 | 149 |
188 | 2171 | 607 | 112 |
189 | 364 | 273 | 61 |
190 | 0 | 630 | 219 |
191 | 2993 | 1379 | 260 |
192 | 0 | 1108 | 350 |
193 | 1964 | 583 | 121 |
194 | 601 | 514 | 206 |
195 | 387 | 216 | 70 |
196 | 1946 | 1593 | 334 |
197 | 545 | 1055 | 190 |
198 | 0 | 399 | 122 |
199 | 838 | 834 | 170 |
200 | 51 | 104 | 73 |
![Use Excel to develop a regression model for the Hospital Database (using the "Excel Databases.xls" file on Blackboard) to predict the number of Personnel by the number of
Births. What can you conclude from the study?
O The number of personnel is not adding significant predictability to the number of births in a hospital.
O The number of births is not adding significant predictability to the number of personnel in a hospital.
O The number of personnel is adding significant predictability to the number of births in a hospital.
O The number of births is adding significant predictability to the number of personnel in a hospital.
QUESTION 10
Now develop a regression model to predict number of Personnel by number of Beds. In comparison to the previous model, which model is stronger at predicting number of
Personnel? Why?
Model 1: Predicting personnel by the number of births
Model 2: Predicting personnel by the number of beds
O Model 1 because the coefficient of determination is higher.
O Model 1 because the coefficient of determination is lower.
O Model 2 because the coefficient of determination is higher.
O Model 2 because the coefficient of determination is lower.](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Feb20a39d-7870-4929-bee1-db66d721f386%2F3242d6d6-5f12-4636-bce8-420a6fd94f36%2Fxsnbvtw_processed.jpeg&w=3840&q=75)
Transcribed Image Text:Use Excel to develop a regression model for the Hospital Database (using the "Excel Databases.xls" file on Blackboard) to predict the number of Personnel by the number of
Births. What can you conclude from the study?
O The number of personnel is not adding significant predictability to the number of births in a hospital.
O The number of births is not adding significant predictability to the number of personnel in a hospital.
O The number of personnel is adding significant predictability to the number of births in a hospital.
O The number of births is adding significant predictability to the number of personnel in a hospital.
QUESTION 10
Now develop a regression model to predict number of Personnel by number of Beds. In comparison to the previous model, which model is stronger at predicting number of
Personnel? Why?
Model 1: Predicting personnel by the number of births
Model 2: Predicting personnel by the number of beds
O Model 1 because the coefficient of determination is higher.
O Model 1 because the coefficient of determination is lower.
O Model 2 because the coefficient of determination is higher.
O Model 2 because the coefficient of determination is lower.
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