1 statistics a find the estimate of the variance in this...

1) Statistics A) FIND THE estimate of the variance, in this case S xy = 10.18, Z1 = 14.97, N = 20, S yy = 173.37 b) calculate the statistical value of T0 with the previous data where Sxx = 0.68 C) Estimate the sum of squares of the SSr regression with the above data Data: N = 20, sum of x = 23.92, sum of x ^ 2 = 29.29, sum of y = 1843.21, sum of y ^ 2 = 170044.53, sum of xy = 2214.66

Transcript

00:01 In this problem we have three questions so let us take a question in part a we are given s xy equal to 10 .18 s y y equal to 173 .37 and that is a sample size equal to 20 and beta 1 which is equal to z1 it is given equal to 14 .97 we have to estimate the variance using this given data now the estimation of variance which can be given by the formula variance is denoted by sigma square so it is given by s s e divided by n minus 2 and it is equivalent to m s e that is mean some of estimates next in the next step we can write this as sigma square equal to s y y minus beta 1 multiplied by s x y divided by n minus 2 so from here after putting in all the values we will get sigma square equal to 173 .37 minus 14 to 14 to point 97 multiplied by 10 .18 whole divided by 20 minus 2.

01:11 After simplifying this expression we get the variance the value of the variance equal to 1 .1653 approximately and this is the answer to part a of the problem.

01:22 Next in part b we have to find the statistic value of t not with s x x equal to 0 .68.

01:32 So here we will use the formula to find t not which is given by b1 beta 1 divided by under root m s e mean some square divided by s x x so putting in the values we will have beta 1 given equal to 14 .97 divided by under root m s e which is nothing but variance so it will 1 .1653 divided by s x x which is given equal to 0 .68 and after simplifying we will have 14 .97 divided by 1 .3097 in the next step to we have the value of t not equal to 11 .4353 approximately and this is the answer to part b of the problem and finally for the last part part b part c we are given n equal to 20 summation x equal to 23 .92 summation x square equal to 29 .29 summation y equal to 1 ,843 .21 summation y square equal to 170 ,44 .53 .53 and summation x y equal to 2 ,214 .66.

03:04 With this given data we have to estimate the sum of of squares of the ssr regression with this data...

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