Please explain how to find the solutions for the questions listed at on the last image shown. Please use the random table below to come up with a sample to use to make the solutions. It's supposed to be a random sample, so please explain how you got the sample from the random table. Please let me know if there is anything missing. Thank you!

Row BATCH 1 BATCH 2 BATCH 3 BATCH 4 JOUDWN 50 . 40 46.4 29.1 37 . 7 156.50 37 .9 43 . 4 2 .5 47.32 18.5 7.1 3.0 63.10 32.9 82.2 7.1 92 . 20 44.9 56 . 4 14.8 217 .10 58 . 8 36 . 6 38 . 6 204 . 90 103.0 24.9 33 . 7 118.20 30 . 5 12.1 51.9 97 . 70 42. 7 53 . 2 51 .9 54 . 20 34.6 17.6 31 . 4 196.00 14.7 26.9 49. 4 69 . 80 12.9 35 . 1 65. 6 81 . 10 34.6 49. 4 21 . 3 61 . 40 69.5 64.9 32.5 103.10 18.0 57 . 4 37.0 44 . 90 79.5 20 .1 28.3 Below is an INTERVAL PLOT for the four BATCHES of 'UNUSUAL OIL RECOVERIES' from 64 Oil Wells. What can be concluded from this graph? Interval Plot of ALL BATCHES vs FACTOR 95% Cl for the Mean 120 100 ALL BATCHES 30 60 40 20 0 2 3 FACTOR The pooled standard deviation is used to calculate the intervals This graph was obtained from a CLASSICAL ONE-WAY ANOVA. You should APPLY the KRUSKAL: WALLIS nonparametric ONE-WAY ANOVA to a sample of size 7 from each of the four BATCHES to confirm what the graph suggests. To do this, you should apply equation 4 to your sample of size 7.SOME EQUATIONS THAT MAY BE USEFUL! 1) Ip = [a(Xi - Xb) (Yi - Yb)] / (n - 1) (Sx Sy) 1a) = [aXiYi - (aXi)(aYi) / n] / (n - 1) ( Sx Sy) NOTE: 1) and 1a) ARE THE SAME EXCEPT ..... 1a) IS EASIER TO COMPUTE! NOTE: Xb is the mean of X, Yb is the mean of Y. 2) Is 1 [ 6 (ad:2)] / N(N2 - 1) NOTE: di is the difference between Rx (rank of X; ) and Ry (rank of Yi). 3) t r(n-2) 1/2 / [ (1 - r2 ) 1/2 ] NOTE: Is or Ip can be used for r. 4) H = 12 0 N(N + 1) aR;2j - 3(N - 1) 5) x2 tot = a(Oi -Ei) 2/ Ei 6) SS = ax;2 - (aXi)2 ; $2 = SS-1 S = ($2 ) 1/2 7) Y = XB 8) SSE = SST - SSR 9) X'Y = X'XB 10) SST = Y'Y - nYb2 11) B = (X'X)-1X'Y 13) SSR = 'X 'Y - nYb2 13) SSE = SST - SSR 14) b1 = (naXiYi - axaYi) /[na X2 ; - (a Xi )2 ] 15) MODEL:Y = bo + b1X 16) bo = Yb - b1Xb where Yb, and Xb are means.\f