Can I get help? as soon as possible please?

Consider the data given below for a paired t-test (assume equal variance). Run/Pair Treatment i = 1 i = 2 d, = y1j - V2j 7.1662 8.2416 -1.0754 2 2.3590 2.4555 0.0965 3 19.9977 21.1018 -1.1041 4 0.9077 2.3401 1.4324 -15.9034 15.0013 0.9021 -6.0722 -5.5941 -0.4781 9.9501 10.6910 -0.7409 -1.0944 -0.1358 -0.9586 4.6907 -3.3446 -1.3461 -6.6929 -5.9303 0.7626 71 = 0.59 V1 = 1.48 Some statistics S, = 10.06 $2 = 10.11 d = -0.890 Sa = 0.398 Pooled StDev S = 10.0848 We may write a statistical model that describes the data from this experiment as: = 1,2 Yu = M + B, +Ey ; = 1,2, 10 where y is the observation at treatment i in a pair j, My is the true mean of observations of the ith treatment, , is the effect on observation due to the j" pair, cy is a random experimental error with mean 0 and variance of (assume equal variance of = of). Note that if we compute the jth difference d, = >1 - yz for all j, the expected value of the difference is: Ha E(dj) = E(1) - E()2)) = ( M1 + Bj) - (12 + Bj) = Hi - H2 That is, in a paired experiment, we may make inferences about the difference in the mean observations of the two treatments My - #2 by making inferences about the mean of the difference Ha. Notice that the additional effect of the pair , cancels out which is a clear advantage of the paired t-test (the principle of blocking).Base on the above discussion, the following hypothesis tests for "no treatment effect" are equivalent in the case of a paired- experiment. Hypothesis Testing A Hypothesis Testing B Ho: M = M2 Ho: Ha = 0 Knowing the equivalence of the above two hypothesis tests in a paired-experiment, answer (solve) the following problems. (a = 0.05) (a) Perform a two-sample t-Test (Hypothesis Testing A) for equal mean My = #2 (assume equal variance). (b) Preform a single sample t-Test (Hypothesis Testing B) for mean Ha = 0. (c) Do you arrive at the same conclusion in the above tests in the case of the data set given in the previous page? If yes, why? If not, why? In answering this question, use terms like "signal", "noise", and "signal to noise ratio". In your discussion, clearly indicate what represents the signal and what represents the noise in each case (a and b)