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Owner: 09carps
Created: Oct 16, 2008
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report of linear and nonlinear data
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The residual plot of the data of wine versus crime shows that the data is not linear. The data table also shows that the plot is not linear when it shows that the correlation is .26. The residual plot of the data of population versus voter turnout shows that the data is linear. The points are randomly scattered below and above zero on the residual plot and also the data table shows that the correlation is .96.

Result 1: wine/crime residuals   [Info]
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Result 2: wine/crime   [Info]
Simple linear regression results:
Dependent Variable: Violent crime rate
Independent Variable: Wine consumption per capita
Violent crime rate = 364.0992 + 99.77388 Wine consumption per capita
Sample size: 35
R (correlation coefficient) = 0.2606
R-sq = 0.06791798
Estimate of error standard deviation: 104.95475
Parameter estimates:
Parameter Estimate Std. Err. DF T-Stat P-Value
Intercept 364.0992 127.843575 33 2.8480055 0.0075
Slope 99.77388 64.342 33 1.5506804 0.1305

Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 26487.977 26487.977 2.4046097 0.1305
Error 33 363511.47 11015.499
Total 34 389999.44

Result 3: population/voter residual   [Info]
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Result 4: population/voter turnout   [Info]
Simple linear regression results:
Dependent Variable: Voters
Independent Variable: Pop x 1000
Voters = 20465.645 + 0.41901916 Pop x 1000
Sample size: 12
R (correlation coefficient) = 0.9591
R-sq = 0.91989267
Estimate of error standard deviation: 4864.405
Parameter estimates:
Parameter Estimate Std. Err. DF T-Stat P-Value
Intercept 20465.645 6582.142 10 3.1092682 0.0111
Slope 0.41901916 0.039102223 10 10.715993 <0.0001

Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 2.71721677E9 2.71721677E9 114.83251 <0.0001
Error 10 2.36624336E8 2.3662434E7
Total 11 2.9538409E9

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