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
   2. Illustrate a simple linear regression using JMP's "Fit-Y-by-X" capability under the Analyze tab. From "Bivariate Fit", select "Fit Line". 5
   3. Describe the results:
      1. Linear Fit - Describe the equation in words. Is there a meaningful intercept?
      2. Summary of Fit - Explain the significance of Rsquare.
      3. Lack of Fit - Using Prob>F and alpha draw conclusions on the null hypothesis "No lack of Fit"
      4. Analysis of Variance - Using Prob>F and alpha draw conclusions on the null hypothesis "Model is not significant"
      5. Parameter Estimates - Explain the findings on the Intercept and slope estimates. 5
   4. Residual Analysis from "Linear Fit":
      1. "Save residuals" and return to data table.
      2. Using Analyze>Distributions, plot the histogram of residuals.
      3. Using Residuals>Continuous Fit>Normal, display normal fit on the residuals.
      4. Using Fitted Normal>Goodness of Fit, determine if the residuals are normal using the Shapiro-Wilk W Test. 5

Bivariate Fit of Concentration By Time 0.5 0.48 0.46 0.44 Concentration 0.42 04 0.38 0.36 10 20 30 40 Time Linear Fit Linear Fit Concentration = 0.4846404 - 0.0026675*Time Summary of Fit RSquare 0.7326 RSquare Adj 0.726234 Root Mean Square Error 0.015737 Mean of Response 0.425227 Observations (or Sum Wgts) 44 D Lack Of Fit Analysis of Variance Sum of Source DF Squares Mean Square F Ratio Model 1 0.02849649 0.028496 115.0683 Error 42 0.01040124 0.000248 Prob > F C. Total 43 0.03889773 <.0001>