After running iterations of lm() in R, I am now stuck with which components of the model's output to present and how to present them. I know that the r-squared value, Co-efficients Plot and Intercept are of central importance. Is there any free resource which shows: how to interpret output, and then visually represent of model outputs,especially output from R. I read Interpretation of R's lm() output but I find it difficult to translate that into what it means in my domain.

My domain is marketing. I am trying to model impact of TV advertising on lead generation. My r-squared value is high but when I plot my coefficients using coefplot in r, they are on the 0 Line. I don't know what to make of it. Happy to share more details & output.

Here is the model output & plots:

Call:
lm(formula = Leads.T ~ ImpressionsM, data = allmodelsetdaily)

Residuals:
Min      1Q  Median      3Q     Max 
-213.81  -60.69   11.81   71.74  178.02 

Coefficients:
Estimate Std. Error t value Pr(>|t|)    
(Intercept)  337.08397   22.22891   15.16   <2e-16 ***
ImpressionsM   0.06898    0.00427   16.15   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 97.15 on 89 degrees of freedom
Multiple R-squared:  0.7457,    Adjusted R-squared:  0.7428 
F-statistic: 260.9 on 1 and 89 DF,  p-value: < 2.2e-16"