Question

Repair Time in Hours Months Since Last Service Type of Repair Repairperson 2.9 2 Electrical Donna Newton 3.0 6 Mechanical Donna Newton 4.8 8 Electrical Bob Jones 1.8 3 Mechanical Donna Newton 2.9 2 Electrical Donna Newton 4.9 7 Electrical Bob Jones 4.2. 9 Mechanical Bob Jones 4.8 8 Mechanical Bob Jones 4.4 4 Electrical Bob Jones 4.5 6 Electrical Donna Newton

1. Develop the simple linear regression equation to predict repair time given the number of months since
the last maintenance service, and use the results to check the conditions necessary for valid inference in
regression, and to test the hypothesis that no relationship exists between repair time and the number of
months since the last maintenance service at the 0.05 level of significance. What is the interpretation of
this relationship? What does the coefficient of determination tell you about this model?

2. Using the simple linear regression model developed in part (1), calculate the predicted repair time and
residual for each of the 10 repairs in the data. Is there any pattern in the residuals for the two types of
repair? Is there any pattern in the residuals for the two repairpersons? Explain.

How do I plot a scatterplot for the residuals to see the pattern for repair type and repairpersons when I only have one column of residuals? What goes on the x and y axis?

Below is my calculation of the residuals.

Thanks!

Answer 1

reguession fiteo Concept and Reasoning The simple linear geegression quadel attemplo to explain and calculate the salationship betrun the two continous variables. A lineal estraight line through the set of n observatione , De Fundamenlāls:- The equatics of the Bomple lêneas sugeeven is y=a+bx. Vleue endicate depend wouiable indicates independent umiable b endicate the slope of the line indicate the ye intercept. b. nExey-Ex Ey & a-Ey-b2x nEx² - (2x)² Hourulay to calculate simple lineae legceision equation tuom the geup infoumaliau bey 2 5.8 20 у x2 ly 2 12.9 4 8:41 5.8 3.0 36 9.00 8 4.8 64. 23.04 38.4 3 1.8 3.24 5.4 2 2.9 48.41 4.9 490 24.01 34.3 9 6.2 81 17.64 37.8 8 4.8 64 23.04 38.4 12.6 4.4 16 1 19.36 36 20.25 27 4.5 6 F2:55 Ey = 38 22x-3033y21564 Sxy=22805

Calculate the values of b and a b=nExy - Ex Ef nEx?_Ex)? 11(228.5)-55x3812 11( 363 -(552 = 0.304) Zy -b za = 38.2-0.30u) (55) 11 = 2.1473 Honce the simple Legeession model is ŷ = 0.1493°+0-304 (2) © Use simple eegeession model to find predicted repair time and residual for each of ten epairs. Begression model Pecelicted Refautime y = 2.1473 +0.3041 (2) y = 2,1493 to 304) (6) Last sevnice 2 2.8 6 1 4.0 426 3.1 11 17 3 2 (3) 2 2.8 (7) 2 9 8 4.3 4.9 a (4) 3.4 o The geaplical sepresentation is

• Type of repair- Electrical *Type of repair-Mechanical 10

It is observed that there is a positive relation occurs between the variables.