Question

In: Statistics and Probability

Days 1 to 120: Number of New Cases 0 1 0 0 2 0 3 0...

Days 1 to 120: Number of New Cases

0 1 0 0 2 0 3 0 0 0 0 14 2 1 0 27 80 51 18 26 216 81 37 117 167 108 151 178 111 414 337 195 706 214 300 68 118 160 190 209 154 193 170 154 166 68 119 152 146 101 98 159 175 195 195 157 130 129 161 116 133 217 209 75 298 240 205 196 233 76 339 170 224 236 188 243 244 151 74 286 261 228 239 211 56 388 363 241 335 337 483 163 332 320 314 312 324 380 210 504 425 450 395 1187 1135 179 1994 1374 1365 1231 1238 908 113 1453 693 1437 1249 1208 597 684

Number of ICU hospitalizations in Houston trauma area (cumulative numbers) (84 data points)

214 134 234 260 237 261 179 235 230 230 219 204 200 202 208 198 197 187 195 207 192 145 193 192 205 200 199 187 187 169 197 178 185 174 172 170 179 191 193 225 207 172 190 195 182 187 199 199 196 205 214 230 221 225 236 224 229 240 240 264 233 231 237 226 264 247 297 319 380 362 374 391 393 430 473 499 540 516 570 596 624 654 667 677

For comparisons with the new cases data set align the two data arrays starting from the end. Data for ICU were not maintained for the same time length as new cases. If we use the previous data sets we have two samples (I would not call them random. They are census data). Define the random variables related to these data sets. What kind of RVs those two are? Using the data above examine if there is an association between these two RVs? If there is one. this would be a linear correlation. Would you call this correlation negative or positive and why? What is the interpretation of your findings in simple words?

Solutions

Expert Solution

R-code :

> x<-c(0, 1, 0, 0, 2, 0, 3, 0, 0, 0, 0, 14, 2, 1, 0, 27, 80, 51, 18, 26, 216, 81, 37, 117, 167, 108, 151, 178, 111, 414, 337, 195, 706, 214, 300, 68, 118, 160 ,190, 209, 154, 193, 170, 154, 166, 68 ,119, 152 ,146, 101, 98 ,159, 175, 195, 195, 157, 130, 129, 161, 116 ,133 ,217 ,209, 75, 298, 240, 205 ,196 ,233 ,76 ,339 ,170 ,224 ,236 ,188 ,243 ,244, 151, 74, 286, 261, 228, 239, 211, 56, 388, 363, 241, 335, 337, 483 ,163, 332 ,320, 314, 312, 324, 380 ,210, 504, 425 ,450, 395, 1187, 1135, 179, 1994, 1374, 1365, 1231, 1238, 908, 113, 1453, 693, 1437, 1249, 1208, 597 ,684)

> x1<-x[37:120]
> y1<-c(214 ,134 ,234 ,260 ,237 ,261 ,179 ,235 ,230 ,230 ,219 ,204 ,200 ,202 ,208 ,198 ,197 ,187 ,195 ,207 ,192 ,145 ,193 ,192 ,205 ,200 ,199 ,187 ,187 ,169 ,197 ,178 ,185, 174, 172, 170, 179, 191, 193, 225, 207, 172, 190, 195, 182, 187, 199, 199, 196, 205 ,214, 230 ,221 ,225 ,236 ,224 ,229 ,240 ,240 ,264 ,233 ,231 ,237 ,226 ,264 ,247 ,297, 319, 380, 362, 374, 391, 393, 430, 473, 499, 540, 516, 570, 596, 624, 654 ,667, 677)
> cor(x1,y1)
[1] 0.708644

orchestra answered 2 years ago
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