Please do work by hand (not in R) and show enough work so I can understand how to do it myself. Thanks.
First, let's solve this by framing null and alternate hypothesis,
The null hypothesis which is H0 => before - after = 0
The alternate hypothesis on the other hand is H1 => before - after <0
1)The mean of the first sample i.e., before the stimulation before =254 And standard deviation SDbefore =95
2)The mean and SD of the second sample are after = 454, SDafter = 451
Now let's proceed to the pooled t-test to test our hypothesis
3)Let us assume that level of significance = 0.05
4) compute the t-statistic
Sp=
==> Sp = 326
t* =
= -1.15
Lets calculate the t critical, t critical at = 0.05 and DOF = 12 is, -1.78 from the table for a left tailed test.
Since t* > t criticle, we accept the H0, Therefore, there is no much difference due to the simulation
Please do work by hand (not in R) and show enough work so I can understand...
Please do question by hand (not in R). Show enough work for me to understand. Thanks. 4. August, Hung, and Houck (1974) studied collagen metabolism in children deficient in growth hormone before and after growth hormone therapy. The data in Table 3.4 are the values of heat-insoluble hydroxyproline in the skin of children before and 3 months after growth hormone therapy. Can we conclude on the basis of these data that growth hormone therapy increases heat-Insoluble hydroxyproline in the skin?...
Please help. Show work so I can understand how to do it Ten pairs of data yield r = 0.003 and the regression equation =2+3x Also, the mean = 5 What is the best predicted value of y for x = 2? 7.0 5.0 8.0 17.0