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Should I be worried about the P-Value Residuals: Min 1Q Median 3Q Max -14875.8 -

ID: 3309653 • Letter: S

Question

Should I be worried about the P-Value

Residuals:
Min 1Q Median 3Q Max
-14875.8 -3624.7 -253.1 6395.8 16165.9

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -142886.8 135323.8 -1.056 0.31181
B 9964.6 1695.2 5.878 7.5e-05 ***
C -2067.5 592.2 -3.491 0.00445 **
D 17863.0 5059.3 3.531 0.00414 **
E -2142.2 2626.9 -0.816 0.43067
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 8954 on 12 degrees of freedom
Multiple R-squared: 0.9623,   Adjusted R-squared: 0.9497
F-statistic: 76.59 on 4 and 12 DF, p-value: 1.943e-08

Explanation / Answer

In above output, we have two types of p-values

1. P-values for individual coefficients:

The p-value for intercept is reported as 0.31181 > 0.05, hence we can conclude that intercept is not significant

The p-value for intercept B is reported as *** i.e. 0, hence we conclude that B is significant and should be in the model.

The p-value for intercept C is reported as ** i.e. 0.001, hence we conclude that C is significant and should be in the model.

The p-value for intercept D is reported as ** i.e. 0.001, hence we conclude that D is significant and should be in the model.

The p-value for intercept E is reported as " " i.e. 0.1, hence we conclude that D is not-significant and should be removed from the model.

2. The second type of p-value presented in above table is p-value for overall model significance (from ANOVA table)

The p-value is 1.946e-08 < 0.05, hence we can conclude that the model is sifnificant.

R-square and multiple R-square are also high, hence model the able to capture most of the variability in the data and we can conclude that this is a good model.

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