first time asking something on cross validated.
I'm doing an analysis on the performance of marketing campaigns. I've done a few linear regressions with the dataset trying to explain as much variance as possible. This is my final model:
all: lm(formula = log(regular.volume.2) ~ ., data = dt.regular.2) Residuals: Min 1Q Median 3Q Max -0.64384 -0.10257 -0.00436 0.11570 0.52346 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.365e+01 1.676e+00 8.150 4.17e-13 *** regular.campaign.b.spend -4.516e-07 3.515e-07 -1.285 0.2013 regular.campaign.e.spend 4.904e-07 3.165e-07 1.550 0.1239 regular.campaign.d.spend 2.568e-07 1.345e-07 1.908 0.0587 . regular.campaign.c.spend -7.104e-08 3.584e-07 -0.198 0.8432 regular.campaign.a.spend 3.853e-07 3.672e-07 1.049 0.2961 regular.campaign.f.spend 6.002e-07 4.789e-07 1.253 0.2125 regular.distribution.2 -2.349e-03 1.650e-02 -0.142 0.8870 regular.display.2 3.250e-02 2.226e-01 0.146 0.8841 regular.feature.and.display.2 1.439e-02 1.705e-03 8.437 9.04e-14 *** regular.feature.2 2.869e-03 1.387e-03 2.069 0.0407 * regular.multibuy.2 -3.908e-04 1.308e-03 -0.299 0.7657 regular.price.2 -1.055e+00 4.944e-02 -21.348 < 2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1978 on 119 degrees of freedom Multiple R-squared: 0.9642, Adjusted R-squared: 0.9606 F-statistic: 266.8 on 12 and 119 DF, p-value: < 2.2e-16
It is my understanding that:
- I have reached a high R², which means I have explained most of the variance.
- A high "estimate" of the independent variable means that it is strongly correlated with the dependent variable.
- A high p-value means that the independent variable it is not statistically significant.
So my question is: what can be said about the campaigns that have a high p-value?
For instance: what can I say about the campaign a, considering that it is not statistically relevant (high p-value)? Can I claim that it hadn't a significant impact on sales, so it should be considered a failure?
tldr: How should I interpret in a business sense the effect of an campaign on sales (linear regression) if this campaigns show a high p-value in a regression which most of the variance has been explained (96%)?
tldr:tldr: help me. I'm desperate.