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Owner: smw_demos
Created: Nov 17, 2013
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Ch 9 Baseball salaries

Here we used the log(salaries) to transform data to achieve linearity.

Result 1: Simple Linear Regression ch 9   [Info]
Simple linear regression results:
Dependent Variable: log(salary)
Independent Variable: Year
log(salary) = -199.85751 + 0.10118811 Year
Sample size: 18
R (correlation coefficient) = 0.94811502
R-sq = 0.8989221
Estimate of error standard deviation: 0.31213746

Parameter estimates:
 Parameter Estimate Std. Err. Alternative DF T-Stat P-Value Intercept -199.85751 16.94869 ≠ 0 16 -11.791915 <0.0001 Slope 0.10118811 0.008482748 ≠ 0 16 11.928694 <0.0001

Analysis of variance table for regression model:
 Source DF SS MS F-stat P-value Model 1 13.863651 13.863651 142.29375 <0.0001 Error 16 1.5588767 0.097429796 Total 17 15.422528

Result 2: Simple Linear Regression ch 9   [Info]

Result 3: Ch 9 resid   [Info]

Data set 1. Ch09_Baseball_Salaries_2012.xls   [Info]