1_)a=3152.95429-3126.1338=26.82044
2) b=
R2adj= | =1-(1-R2)*(n-1)/(n-k-1)= | 0.9908 |
3)
c=1.57501*59.77=94.1383
4)
d=-1.26615/0.0386=-32.8018
5)
e=-1.26615-(-1.19239+1.26615)=-1.33991
3 (20%) Brian once fits a simple regression model, but the printout is somehow incomplete due...
4. Let’s compare the results you calculated for Q3b with results from a multiple linear regression. 4a. Would additionally controlling for ‘depth’ and ‘latitude’ be helpful? In other words, is a model that includes ‘depth’, ‘latitude’ and ‘longitude’ superior in model fit to a model that includes only ‘longitude’? Output for a multiple linear regression which includes longitude, depth, and latitude is provided below. (2 points) 4b. Interpret the parameter estimate for ‘longitude’ from the multiple linear regression output. (1...
Which model is more appropriate for these data: the model in SAS Output 1 or the model in SAS Output 2? Which test statistic and p-value should you use to make this decision? Output 1 because the interaction is not significant (F = 0.92, p-value = 0.4594). Output 1 because the interaction is not significant (F = 6.25, p-value = 0.0003). Output 1 because the interaction is significant (F = 6.25, p-value = 0.0003). Output 2 because the interaction is...
can you answer question 9 please Problems 473 results from parts (a), (b), and (c). What model seems most plausible? How do the data limit your conclusions? tle the data from Freund (1979), presented in Problem 22 in Chapter 14. Taking be model discussed there as the maximum model, repeat parts (a) through (h) of Problem 6. In part (h), note the possible role of collinearity. A random sample of data was collected on residential sales in a large city....