13.50 The owner of a moving company typically has his most experienced manager p

Question

13.50 The owner of a moving company typically has his most experienced manager predict the total number of labor hours that will be required to complete an upcoming move. This approach has proved useful in the past, but the owner has the business objective of developing a more accurate method of predicting labor hours. In a preliminary effort to provide a more accurate method, the owner has decided to use the number of cubic feet moved and the number of pieces of large furniture as the independent variables and has collected data for 36 moves in which the origin and destination were within the borough of Manhattan in New York City and the travel time was an insignificant portion of the hours worked.

E: Determine whether there is a significant relationship between labor hours and the two independent variables (the number of cubic feet moved and the number of pieces of large furniture) at the 0.05 level of significance

F: Determine the p-value in (e) and interpret its meaning.

G: Interpret the meaning of the coefficient of multiple determination in this problem

H: Determine the adjusted r2.

I: At the 0.05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. Indicate the most appropriate regression model for this set of data

J: Determine the p-values in (i) and interpret their meaning

K: Construct a 95% confidence interval estimate of the population slope between labor hours and the number of cubic feet moved. How does the interpretation of the slope here differ from that in Problem 12.44 on page 443?

L: What conclusions can you reach concerning labor hours?

Explanation / Answer

Solution-

Since the data has not been provided, i will write the general answers for the questions above-

To test the sifnificance of the model, we need to take into account the value of F statistic and the critical value concerning the test. If F statistic is greater than the critical value, then null hypothesis is rejected and thus we can conclude that there is a significant relationship between the independent and dependet variables.

Or we can calculate the p-value- It will be calculated as-

P( Fdf1, df2 > value of F statistic) using the F tables. If p-value is less than the the level of significance, then null hypothesis is rejected and thus we can conclude that there is a significant relationship between the independent and dependet variables.

COfficient of determination helps to tell the the percentage of variation in the dependent variable explained by the model. A value greater than 0.8 gives the idea that model is a good fit.

Individual significance of the each of the independent variable can be tested using the value of standard error of each variable and then calculating the value of test statistic. Then we need to compare this value with the critical value obtained from t tables.  If value of t statistic is greater than the critical value, then null hypothesis is rejected and thus we can conclude that individual independent variable is significant.

Thanks!

Related Questions

Navigate

• Browse (All)
• Browse 1
• Subjects

Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.