1.
A computer manager needs to know how efficiency of her new computer program depends on the size of incoming data and how many tables are used to arrange each data set. Efficiency will be measured the number of processed requests per hour. Applying the program to data set of different sizes and number of tables are used, she gets the following results. a) Interpret the values of regression coefficients b1 and b2. b) Test the significance of the regression model at 0.05 level of significance. c) Is there significant relationship between processed request and number of tables at 0.05 level of significance? Given standard error of b2=0.55. d) What percentage of variation of processed requests is explained by data size and number of tables? e) Compute standard error of estimate. f) Estimate the number of processed requests if data size is 9 gigabytes and number of tables used are 8. The regression equation obtained is $Y = 52.7 - 2.87 X_1 + 0.85 X_2$. Total sum of square = 1452, Sum of square due to regression = 1143.3.
$\begin{array}{|c|c|c|c|c|c|c|c|} \hline \text{Processed requests, Y} & 16 & 26 & 17 & 41 & 50 & 55 & 40 \\ \hline \text{Data size, (gigabytes), X1} & 15 & 10 & 10 & 8 & 7 & 7 & 6 \\ \hline \text{Number of tables, X2} & 1 & 2 & 10 & 10 & 20 & 20 & 4 \\ \hline \end{array}$
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