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Owner: 10steck
Created: Oct 16, 2008
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Views: 1175
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The variables for weight and mpg seem to be linear, negatively, strongly associated. The residual plot proves a linear trend because there is no pattern in the plot. Also, the value of r= -0.8666 which proves a strong negative association.

Result 1: Residual for Weight/MPG   [Info]
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Result 2: Simple Linear Regression Data for Weight/MPG   [Info]
Simple linear regression results:
Dependent Variable: mileage
Independent Variable: weight
mileage = 45.64536 - 0.005222044 weight
Sample size: 25
R (correlation coefficient) = -0.8666
R-sq = 0.7509587
Estimate of error standard deviation: 3.016149
Parameter estimates:
Parameter Estimate Std. Err. DF T-Stat P-Value
Intercept 45.64536 2.6027584 23 17.537302 <0.0001
Slope -0.005222044 6.27053E-4 23 -8.327914 <0.0001

Analysis of variance table for regression model:
Source DF SS MS F-stat P-value
Model 1 630.9254 630.9254 69.35415 <0.0001
Error 23 209.23456 9.097155
Total 24 840.16

Result 3: Scatter Plot of Weight/MPG   [Info]
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Data set 1. car_weight_and_mileage.XLS   [Info]
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<A href="">Weight/MPG</A>

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