regression analysis problem?

Question

How do you solve this?
Months Since Last ServiceType of RepairRepairpersonRepair Time In Hours
4ElectricalBob5
8ElectricalTom7.5
10ElectricalTom8.4
2MechanicalTom3.3
1MechanicalTom3.7
5ElectricalBob5
7MechanicalDave7.3
7ElectricalBob5.8
10ElectricalTom8
5ElectricalTom5.8
10MechanicalBob10.1
6ElectricalTom5.6
4ElectricalDave6.3
6MechanicalDave7.4
1MechanicalTom4.3
10ElectricalDave8.7
5ElectricalTom4.4
2ElectricalTom4
9ElectricalDave7.8
1MechanicalBob4.3
7MechanicalBob7.8
5ElectricalDave5.4
4MechanicalTom5
6MechanicalDave7.8
1ElectricalBob3.9
2MechanicalDave5.2
3MechanicalTom5.2
2MechanicalTom3.3
9ElectricalBob7
3ElectricalDave5.4
4MechanicalBob5.4
5ElectricalTom5.9
a. Develop a regression model explaining the repair time based upon the number of month
b. Develop a simpler regression model by eliminating any factor the is not significant using an α = 0.05.
c. Using both models above, generate a 95% confidence interval on the repair time for an auto which was last serviced 5 months ago which requires electrical repair assuming Dave is the repair person.

Answer 1

I don't, you do.
In part a, y, is the repair time (predicted variable) and x is the number of months. You're just going to have to crank out the variances and cross-variances (or use a canned program on the computer) to come up with your line.
In part b, you are going to look for "outliers" y values.
There is a equation to give the confidence interval of y based on the "error" after the initial variance of y is adjusted for the error removed by the regression line.
After the outliers are tossed out, you go back and develop another regression line.
In part c, you calculate the interval at 5 months service. The simpler model should give a narrower band.

Answer 2

this may well be a very straightforward question. it is likewise impossible to respond to over Yahoo! solutions. it extremely is in basic terms too complicated. set up the scatter diagram using the merchandising and sales records on my own. forget approximately the different records. you in basic terms ought to discover the regression equation instructions. Write the equation out of the slope, variables and constants. it extremely is going to assist you to think of throughout the time of the meaning of the completed equation. you should confirm the equation using the consequence being $4,999,000. it extremely is in basic terms straightforward algebra from severe college. the extensive-unfold blunders of the estimate is greater durable. it extremely relies upon how extensive the unfold of the blunders are in estimating the real slope b1. on your case, the blunders are extremely great so it extremely is going to result the extensive-unfold of your estimate. back, look this up on your stats e book.