a director wants to understand if variable tv is a significant linear predictor of texting with

Step 1: The model is a linear regression model with Day1Survey$Texting as the dependent variable

Question

Call: lm(formula = Day1Survey$Texting ~ Day1Survey$TV) Residuals: Min 1Q Median 3Q Max -84.621 -19.369 -6.073 9.536 207.941 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 5.679 9.052 0.627 0.53389 Day1Survey$TV 5.197 1.267 4.101 0.00019 * --- Signif. codes: 0 * 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '' 1 Residual standard error: 43.85 on 41 degrees of freedom Multiple R-squared: 0.2909, Adjusted R-squared: 0.2736 F-statistic: 16.82 on 1 and 41 DF, p-value: 0.00019

          Call:
lm(formula = Day1Survey$Texting ~ Day1Survey$TV)
Residuals:
Min 1Q Median 3Q Max
-84.621 -19.369 -6.073 9.536 207.941
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 5.679 9.052 0.627 0.53389
Day1Survey$TV 5.197 1.267 4.101 0.00019 ***
---
Signif. codes: 0 *** 0.001 '**' 0.01 '*' 0.05 '.' 0.1 '' 1
Residual standard error: 43.85 on 41 degrees of freedom
Multiple R-squared: 0.2909, Adjusted R-squared: 0.2736
F-statistic: 16.82 on 1 and 41 DF, p-value: 0.00019

a director wants to understand if variable tv is a significant linear predictor of texting with 95 confidence 1 what is fitted regression equation 2 interpret value 5197 what does it stand f 50804

Added by Gregorio W.

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