For this problem, collect data on any variables of interest(sample size for each group of the two groups n=>30) and performa two-sided significance test for comparing two independentpopulation means. You can also simulate your own data. Address thefollowing:
a. A brief introductory paragraph describing the problem.Remember that you want to think of an experiment where you’recomparing 2 independent groups, such as, for example, “thepopulation mean speed for runners using training method A versusrunners using training method B.” There is a clinical trial of adrug that is supposed to significantly reduce you cholesterol andthe two groups
b. Set up your framework in a null and alternative hypothesisusing symbols and notation as they are presented in the textbook.For the null, traditionally should have the general set-up of H0:µ1 = µ2 An example of this could be “µA = the population mean speedfor runners using method A is equal to µB = the population meanspeed for runners using method B.” H1: can have a <, or >, or? depending on what you choose to test. Using the example above, ifyou want to test that A is greater than B, then do: H1: µA >µB
c. A paragraph describing how you collected the data (i.e., thenumber of observations, time of day, etc. Please present the rawdata in a table.
d. Create a graph of the means of the two samples using Excel.Clearly label your axes, and give your figure a title.
e. A section explaining the results of the analysis (calculatedstatistics, and p-values). Based on what you find, state yourdecision (whether you reject or fail to reject the H0) andconclusion (whether you have sufficient or insufficient evidencefor H1).
f. Describe how would you change the experimental design tobecome dependent or related samples? Think about which factors youcould possibly control for that weren’t controlled for in theinitial analysis. For example, instead of comparing 2 independentgroups of runners using method A vs. B, we could “match” runnersacross groups according to age, experience, education, height, etc.This approach is more complicated, but worth describing how itcould be done.
