Adult mortality rate is described as the probability of dying between 15 and 60 years of age per 1000 population.

In this project, you are given the adult mortality rates from a random sample of 101 countries in the world from years 2000 and 2015.

The data is disaggregated based on gender for each year.

Part 1 Data: Download the Adult Mortality Data spreadsheet and study the data. (Listed below)

Based on the data set provided (above), produce the following output with SPSS: Generate descriptive statistics for: Male, Female, and Both Sexes from 2000 and 2015 data.

Generate comparative boxplots for: Male data between 2000 and 2015, Female data between 2000 and 2015, Both Sexes data between 2000 and 2015

Using the data from 2000, estimate the mean adult mortality rates for male, female and both sexes for the world population with 95% confidence.

Using the data from 2015, estimate the mean male, female and both sexes adult mortality rates for the world population with 95% confidence.

Estimate the mean difference (with 95% confidence) between: Male adult mortality rates of 2000 and 2015, Female adult mortality rates of 2000 and 2015, Both sexes adult mortality rates of 2000 and 2015

Test the hypothesis that the mean male adult mortality rates between 2000 and 2015 are different with a hypothesized mean difference of 30.

Test the hypothesis that the mean female adult mortality rates between 2000 and 2015 are different with a hypothesized mean difference of 30.

Test the hypothesis that the mean adult mortality rates for both sexes between 2000 and 2015 are different with a hypothesized mean difference of 30.

2000

Male

88 91 96 99 99 99 100 102 104 106 110 113 119 119 124 126 127 128 132 132 135 138 142 145 145 146 150 157 160 160 174 177 179 179 180 181 183 187 190 195 196 199 200 208 210 213 218 226 231 240 241 241 242 242 243 247 248 250 251 252 261 265 273 274 281 287 293 296 298 298 305 307 314 314 322 326 329 337 354 356 372 374 382 402 410 412 430 431 437 466 473 524 577 594 641 654 655 712 443 301 256

Female

56 48 67 57 54 56 80 61 57 68 71 88 91 49 94 68 64 96 69 97 70 92 62 63 83 70 128 100 104 89 89 169 94 74 137 133 140 101 102 147 174 93 79 158 166 157 87 99 133 109 145 137 143 103 140 140 142 140 194 198 184 176 163 210 223 280 300 105 246 193 309 132 239 121 116 219 286 275 296 135 321 293 329 359 378 170 378 401 379 450 446 333 499 582 654 575 675 433 158 145 220

Both Sexes

73 70 88 78 76 78 92 82 80 87 96 107 106 84 110 98 96 112 101 115 103 115 103 105 114 110 139 127 138 125 131 173 137 127 155 156 160 144 149 172 185 142 139 183 188 186 153 163 182 175 192 189 192 175 192 194 197 198 224 224 222 221 219 243 250 284 296 200 272 246 307 218 274 218 218 274 308 305 325 247 346 335 355 380 394 292 404 416 408 457 461 426 536 588 647 614 665 593 307 225 238

2015

Male

64 70 75 74 75 71 74 78 70 80 98 81 91 99 93 78 85 111 93 98 110 113 104 102 128 98 79 124 110 130 145 151 153 131 137 154 104 131 167 166 181 165 185 167 204 181 166 187 185 191 193 237 188 202 174 192 216 205 216 217 240 234 272 217 225 236 239 244 252 256 266 262 209 177 226 307 274 270 265 294 283 312 340 351 377 279 378 288 362 311 414 313 425 398 298 360 359 289 325 231 187

Female

42 34 47 44 41 39 59 50 37 53 58 57 65 45 79 48 45 83 55 71 53 70 51 49 77 51 43 74 70 72 88 105 80 60 97 108 86 80 79 126 151 78 68 109 147 129 67 83 97 74 100 132 105 76 104 105 123 116 142 164 158 138 145 154 156 199 219 87 202 173 267 105 143 61 82 136 224 211 215 98 234 236 283 313 338 118 333 245 308 245 377 152 326 330 212 242 313 222 118 102 143

Both Sexes

53 52 68 59 58 55 69 64 54 66 81 75 78 72 88 63 65 98 74 85 82 92 78 76 103 74 61 98 99 102 116 129 116 95 114 130 95 106 123 146 166 118 127 138 176 156 117 137 142 133 145 184 147 138 139 148 170 161 181 190 198 188 211 186 188 220 229 165 227 215 266 178 174 119 153 222 249 240 241 196 258 275 312 332 357 198 356 267 335 279 397 227 373 365 256 303 336 255 222 166 165