Question

 

A new drug has been developed to treat a particular condition, and it is alleged to be more effective than traditional treatment. An experiment will be conducted to test whether the claim is true. To perform the hypothesis test, a 99% confidence level is selected for the hypothesis test. The new drug will be administered to a sample of 200 individuals with the condition, selected at random. Another 300 individuals are randomly selected to receive the traditional treatment.

Of the 200 individuals treated with the new drug, 140 were completely cured. Of those treated with the traditional method, 180 were completely cured.

a. Is there statistical evidence to support the claim that the new drug is more effective? Take the proper test and finish

b. If you were a patient of this condition, which treatment would you select? Justify your answer

Answer 1

As we are doing the test at 99% confidence level, therefore 0.01 is the level of significance here.

a) The sample proportions here are computed as:
p1 = 140/200 = 0.7
p2 = 180/300 = 0.6

The pooled proportion here is computed as:
P = (140 + 180) / (200 + 300) = 0.64

The standard error here is computed as:

Therefore the test statistic here is computed as:

As this is a one tailed test, the p-value here is computed from the standard normal tables as:
p = P(Z > 2.28) =0.0113

As the p-value here is 0.0113 > 0.01 , which is the level of significance, therefore the test is not significant here and therefore we cannot reject the null hypothesis here. Therefore we dont have sufficient evidence here that the new drug is more effective

b) Given that the two drugs have no significant different treatment rates, we can go with any drug out of the two drugs here.