1. A nationwide CDC report stated that 35% of all hospitalizations due to foodborne illness were caused bySalmonellainfection. A study of 1000 hospitalizations from foodborne illness within a specific healthcare system found that 327 were caused bySalmonellainfection. The researchers in the study wanted to test if the proportion ofSalmonella-caused hospitalizations in their system was significantly less than that reported by the CDC.

The researchers obtained the following results:

> prop.test(x=327, n=1000, p=0.35, alternative="less", correct=FALSE) 1-sample proportions test without continuity correction data: 327 out of 1000, null probability 0.35 X-squared = 2.3253, df = 1, p-value = 0.06364 alternative hypothesis: true p is less than 0.35 95 percent confidence interval: 0.0000000 0.3518394 sample estimates: p 0.327 > qnorm(0.05) [1] -1.644854

What would the p-value be for the hypothesis test of whether the proportion ofSalmonella-caused hospitalizations in their system was significantly different from that reported by the CDC.

a. 0.06365

b. 0.327

c. 0.2546

d. 0.1273

2.

Group	Disease	No Disease	Total
Group 1	X	100	154
Group 2	6	20	26
Group 3	24	52	76
Total	84	172	256

The p-value for the chi-squared test of independence is 0.467.

Which of the following is the best interpretation of this p-value?

a. If the grouping variable is independent of the disease status, we would expect to see this imbalance of disease status or more extreme 46.7% of the time.

b. The probability of the null hypothesis being true is 0.467

c. We should reject the null hypothesis that the grouping variable is independent of the disease status

d. There is a 46.7% chance that disease status is dependent upon the grouping variable.

3. Use the table below to find the odds ratio of death for those who in the control group compared to those in the treatment group?

	Control	Treatment	Total
Alive	4	24	28
Dead	30	45	75
Total	34	69	103

a. 2.8

b. 0.36

c. 4

d. 0.25