Question

A pharmaceutical company developed a new revolutionary diet pill, “fat buster,” which is believed to greatly help people with losing weights. They conducted an experimental study to assess its relative effectiveness, comparing it with a currently popular diet pill in the market. A random sample of 28 participants were split into two groups: People in Group A used this company’s “fat buster” and those in Group B used a competing diet pill, “fat killer.” After taking the pills for 6 months while otherwise being treated the same way, participants had their weights measured. On average, participants in Group A lost 11.39 pounds while those in Group B lost 6.71 pounds. The results of t-test (non-directional), however, were not significant (a = .01, t_crit = 2.779): t (26) = 2.509. Anxious and desperate, the company now wants to consult you as the new expert on statistics. What recommendations would you make to help them obtain significant results? Provide at least two recommendations. Any additional (and valid) suggestions or recommendations you provide will be given 2 extra points for each.

Answer 1

• RECOMMENDATIONS:

1. We can set
   to make the acceptance region more shorten.
2. Though the samples are homogeneous in nature, but there might prevail some issues with the sample i.e
   due to randomness may be slim people such that who didn't have enough fat to loss were chosen for the new drug or fatty people such that who are more prone towards loosing weight for the previous drug were chosen , which resulted the failure of the test.
3. There may be some outliers in the data which resulted in failure of the test, in such a case trimmed mean may be used in stead of the true sample mean
4. Though the test is not rejected i.e., the means are same, but the previous drug may cause more variation than the new drug So, by testing the following hypothesis i.e. the new drug may be more efficient than the previous drug -
   VS   
   where  = variance of the new drug,   =variance of the previous drug
   the efficiency of the new drug may be observed.
   
   
   I hope this answer helps you to a great extent. If you have any query, comment below. Hit the Like button if you' re satisfied. Thank You. :)