Q Which model the single explanatory variable linear model or the multiple explanatory variable linear model explains more of the variation in travel time for this sample of drivers I need help for this part Multiple linear regression results Dependent Variable Travel Time (minutes) Independent Variable(s) Distance Traveled (miles), Number of Deliveries Travel Time (minutes) 2 8424328 3 972593 Distance Traveled (miles) 27 087275 Number of Deliveries Parameter estimates Parameter Estimate Std Err Alternative DF T Stat P value Intercept 2 8424328 53 455847 0 17 0 053173469 0 9582 Distance Traveled (miles) 3 972593 0 42970343 0 17 9 2449646 0 0001 Number of Deliveries 27 087275 8 5109593 0 17 3 1826348 0 0054 Analysis of variance table for multiple regression model Source DF SS MS F stat P value Model 2 119399 34 59699 672 44 958841 0 0001 Error 17 22573 856 1327 8739 Total 19 141973 2 Summary of fit Root MSE 36 440004 R squared 0 841 R squared (adjusted) 0 8223 a Which model the single explanatory variable linear model or the multiple explanatory variable linear model worked better for Driver 6 Justify your answer The multiple explanatory variable linear model worked better for Driver 6 because prediction value is closer to driver's actual travel time (This is what I think for multiple explanatory variable , but getting stuck for above question)

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Q# Which model - the single explanatory variable linear model or the multiple explanatory variable linear model - explains more of the variation in travel

Q# Which model - the single explanatory variable linear model or the multiple explanatory variable linear model - explains more of the variation in travel time for this sample of drivers? I need help for this part.

Multiple linear regression results:

Dependent Variable: Travel Time (minutes)

Independent Variable(s): Distance Traveled (miles), Number of Deliveries

Travel Time (minutes) = 2.8424328 + 3.972593 Distance Traveled (miles) + 27.087275 Number of Deliveries

Parameter estimates:

Parameter

Estimate

Std. Err.

Alternative

T-Stat

P-value

Intercept

2.8424328

53.455847

0.053173469

0.9582

Distance Traveled (miles)

3.972593

0.42970343

9.2449646

<0.0001

Number of Deliveries

27.087275

8.5109593

3.1826348

0.0054

Analysis of variance table for multiple regression model:

Source

F-stat

P-value

Model

119399.34

59699.672

44.958841

<0.0001

Error

22573.856

1327.8739

Total

141973.2

Summary of fit:

Root MSE: 36.440004

R-squared: 0.841

R-squared (adjusted): 0.8223

a.Which model - the single explanatory variable linear model or the multiple explanatory variable linear model - worked better for Driver #6? Justify your answer.

The multiple explanatory variable linear model worked better for Driver #6 because prediction value is closer to driver's actual travel time.(This is what I think for multiple explanatory variable , but getting stuck for above question).