A company that manufactures computer chips wants to employ a multiple regression model to study effect that two different variables have on y, the total daily production cost (in thousands of dollars). Let β1 as well as β2 denote the coefficients of 2 variables in this model. Using 16 observations on each of variables, the software program employed to find out the estimated regression model reports that the total sum of squares (SST) is 360.44 and regression sum of squares (SSR) is 84.16. Using significance level of 0.10, can you conclude that at least one of independent variables in model offers useful (ie statistically significant) information for predicting daily production costs?
Carry out a one-tailed test, carry imtermediate computations to at least 3 decimal places and round answers for the responses below.
The null hypothesis: Ho:
The alternative hypothesis: H1:
The type of test statistic:
The p-value (round to at least 3 decimal places)
Can you conclude that at least 1 of the independent variables in the model provides useful information for predicting daily prodution costs? Yes or No