Question

Question:

1. Assume the data in tab 11.a (Cancer mortality) represent data on cancer mortality rates for the communities in your hospital's service area. Perform a statistical test to determine if the average cancer mortality in the rural communities is different from the average mortality in the urban communities. (Assume the mortality rates are normally distributed.) Offer an interpretation of your results. Remember to describe the mean cancer mortality rates. (4 points)
2. Does this problem call for a one-tailed test or a two-tailed test? (1 point)
3. Using the data in tab 11.b (Weight loss), test whether the average weight of patients attending your new weight loss clinic has changed as a result of attending the clinic. That is, is the average weight of patients after attending the clinic different from the average weight before attending? Report the average weight of these patients before and after attending the clinic and interpret the results of the statistical test(s) performed. (5 points)
4. Apply the appropriate t-test to compare the mean time required to process clinical records before and after the introduction of a new method for this work. Note, assume the same records were processed before and after the introduction of the new procedure. Using data in Tab 12. (Processing time), evaluate the following:
5. Test whether the intervention designed by a clever intern to reduce the time required to process billing forms made a difference. (That is, test whether the mean processing time after the intervention is different from the mean before the intervention.) Report your results and offer an interpretation of the statistical test(s) performed. (5 points)
6. Would your conclusion be different if you were asked to test whether mean processing time after the intervention was less than mean processing time before the intervention? Describe how you interpret your results under these conditions. (Hint: this is a one-tailed problem.) (5 points)
7. Choose the appropriate t-test for your evaluation and decide if each hypothesis requires a one- or a two-tailed test. Assume the data in Tab 13.(ER Wait times) are the time spent waiting to be seen by a physician for two groups of patients. One group were considered to have true emergencies and the other group were triaged as requiring only urgent care.
8. Test the hypothesis that the time spent waiting does not depend on the reason for admission to the ER (true emergency v. needing urgent care). Report your results and interpret the statistical test. Does this hypothesis call for a two-tailed test or a one-tailed test? (5 points)
9. Test the hypothesis that waiting time for patients with true emergencies was less than the waiting time for patients only needing urgent care. (Note the specific hypothesis to be tested here.) Interpret the results of the proper statistical test and justify your answer. Does this hypothesis call for a one-tailed or a two-tailed test? Please justify your answer.

PLEASE USE DATA BELOW

ER waiting time:

Type of visit:

Urgent   Emergency
29 33
30 43
32 26
31 46
22 31
26 40
30 34
38 4
29 30
28 24
29 40
38 32
30 36
43 31
23 45
32 20
25 31
32 42
30 29
32 40
35 34
34 44
29 9
21 25
29 29
31 34
36 28
14 37
31 18
36 38
29
48
36
49
28
39
34
37
34
42

**The last Data Set of numbers refer to Column 2 (Emergency)**

Answer 1

S.no	Urgent	Emergency
1	29	33
2	30	43
3	32	26
24	21	25
25	29	29
26	31	34
27	36	28
28	14	37
29	31	18
30	36	38
31	29
32	48
33	36
34	49
35	28
36	39
37	34
38	37
39	34
40	42
Mean	32.025	31.76666667
sd=	6.787951	9.919271849
Count	40	30