The data come from the Western Collaborative Group Study, which was carried out in California in 1960-61 and studied 3,154 middle-aged men to investigate the relationship between behaviour pattern and the risk of coronary heart disease. These particular data were obtained from the 40 heaviest men in the study (all weighing at least 225 pounds) and record cholesterol measurements (mg per 100 ml), and behaviour type on a twofold categorization. In general terms, type A behaviour is characterized by urgency, aggression and ambition, while type B behaviour is relaxed, non-competitive and less hurried. The question of interested is whether, in heavy middle-aged men, cholesterol level is related to behaviour type.
233 291 312 250 246 197 268 224 239 239 254 276 234 181 248 252 202 218 212 325
344 185 263 246 224 212 188 250 148 169 226 175 242 252 153 183 137 202 194 213
Use the resampling methods studied in classes and perform the analyses in SAS to answer the following questions:
(a) Does the Type A behaviour group differ from the Type B group in terms of their average cholesterol level? Justify your answer. Include the corresponding hypotheses and histogram, indicating in it clearly the statistic used for the test.
(b) If there is a difference on average on the cholesterols levels of Type A and B groups in the analysis performed previously, calculate a 95% bootstrap confidence interval. Interpret your results.
(c) What is your advice as analytics specialist? Justify your answer. Write a brief report with your findings.
(d) The patients of group A have voluntarily participated in a therapy in order to change positively their behaviour. Some previous studies were used to convince them. The therapy is new and it has not been tested before. Their initial and final cholesterol levels, i.e., before and after the therapy, were registered and are displayed in the table below:
Patient 1 2 3 4 5 6 7 8 9 10
Before 233 291 312 250 246 197 268 224 239 239
After 247 283 282 185 254 172 243 221 234 240
Patient 11 12 13 14 15 16 17 18 19 20
Before 254 276 234 181 248 252 202 218 212 325
After 259 279 215 129 237 234 178 165 188 310
You as a data analyst have to assess the therapy. What would you conclude? Write a brief report with your findings. This should answer the following questions: was the therapy effective for all the patients in the study?; is the therapy effective?; if so, quantify the difference between the groups. Justify all your conclusions.
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