1. Using the "Westwood Man-hours data.jmp" file perform a simple linear regression:
   1. Describe what you find out about the field relationships using Distributions under JMP's Analyze tab to just look at the data. Is there a relationship possibly? How strong? 5
      

Distributions 40 Man-Hours (Y) 40 Lot Size (X) 200- 90 80 70 150 Man-Hours(Y): [125, 150) 60 N:3 50 100 40 30 50- 20 10- Quantiles Quantiles 100.0% maximum 181 100.0% maximum 80 99.5% 181 99.5% 80 97.5% 181 97.5% 80 90.0% 176.9 90.0% 79 75.0% quartile 138.5 75.0% quartile 62.5 50.0% median 105 50.0% median 55 25.0% quartile 77 25.0% quartile 30 10.0% 47 10.0% 21 2.5% 45 2.5% 20 0.5% 45 0.5% 20 0.0% minimum 45 0.0% minimum 20 Summary Statistics Summary Statistics Mean 1084 Mean 50 Std Dev 40.03665 Std Dev 19.436506 5td Err Mean 12.6607 5td Err Mean 6.146363 Upper 95% Mean 137.04049 Upper 95% Mean 63.904039 Lower 95% Mean 79.759506 Lower 95% Mean 36.095961 N 10 N 10Bivariate Fit of Man-Hours (Y) By Lot Size (X) 200 150 Man-Hours(Y) 100 50- 10 20 30 40 50 60 70 80 Lot Size (X) Linear Fit Linear Fit Man-Hours(Y) = 11.194118 + 1.9441176*Lot Size (X) 4 Summary of Fit RSquare 0.890771 RSquare Adj 0.877117 Root Mean Square Error 14.0347 Mean of Response 1084 Observations (or Sum Wats) 10 Lack Of Fit Sum of Source DF Squares Mean Square F Ratio Lack Of Fit 5 807.1157 161.423 0.6300 Pure Error 768.6667 256.222 Prob > F Total Error 1575.7824 0.6965 Max RSq 0.9467 Analysis of Variance Sum of Source DF Squares Mean Square F Ratio Model 1 12850.618 12850.6 65.2406 Error 8 1575.782 197.0 Prob > F C. Total 9 14426400 <.0001 parameter estimates term estimate std error t ratio prob> |t| Intercept 11.194118 12.82693 0.87 0.4083 Lot Size (X) 1.9441176 0.240693 8.08 <.0001>