IS Client type has three levels.) a? Which model would you recon y=Net profit earned from the client X4 = Number of hour

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IS Client type has three levels.) a? Which model would you recon y=Net profit earned from the client X4 = Number of hour

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Is Client Type Has Three Levels A Which Model Would You Recon Y Net Profit Earned From The Client X4 Number Of Hour 1
Is Client Type Has Three Levels A Which Model Would You Recon Y Net Profit Earned From The Client X4 Number Of Hour 1 (29.22 KiB) Viewed 17 times
Is Client Type Has Three Levels A Which Model Would You Recon Y Net Profit Earned From The Client X4 Number Of Hour 2
Is Client Type Has Three Levels A Which Model Would You Recon Y Net Profit Earned From The Client X4 Number Of Hour 2 (37.51 KiB) Viewed 17 times
IS Client type has three levels.) a? Which model would you recon y=Net profit earned from the client X4 = Number of hours spent working with the client X2 = Type of client (1 if manufacturing, 2 if service, 3 if governmental) Complete the regression model b DO у 2,346 4,300 272 1,215 1,405 400 -750 3,459 2,472 1,973 204 X 47 58 29 58 23 24 35 43 45 27 33 X2 1 2 3 2 2 3 3 NON NGON und the x coefficient to two decin 2 3 model provides a better fit.

In an effort to explain variation in client profitability, an accounting firm collected the data shown in the accompanying table. The firm wants to know if it needs the client type in addition to the number of hours spent working with the client to predict the net profitamed from the client Fit a model to the data that incorporates the number of hours spent working with the client and the type of cient as independent variables (Nint Client type has three levels.) b. Fit a second-order model to the data, using the same dummy variables for client type. Does this model provide a better fit than that found in part a? Which model would you recommend be used? Click the loon to view the data CHE 0 Since client type has three levels, use two dummy variables for client type, xx* 1 if manufacturing, 0 otherwise and x 11 sovke, otherwise. Complete the regression model below. 0-0-0xxx (Round the constant and the X and X, coefficients to the nearest integer as needed Round the x coefficient to one decimal place as needed) b. Complete the regression model below. 9+0+ (Ox+Ox Ox+x (Round the constant and the xy and my coefficients to the nearest integer as needed. Round the x, conficient to one decimal place as needed. Round the x coafficient to two decimal places as needed.) The adjusted R-squared value for the first-order model is and the adjusted Resouared value for the second-order model is 1.50 W model provides a better fit (Round to three decimal places as needed.) V significant in the first-order model in the second-order model significant. So model is effective at explaining variation in the dependent variable, client profitability. Therefore, recommend model For = 0.05,
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