##
## ===============================================
## Dependent variable:
## ---------------------------
## Loyalty * 100
## -----------------------------------------------
## Tweets -0.00000**
## (0.00000)
##
## Reactions 0.00003***
## (0.00001)
##
## Episodes 0.088*
## (0.047)
##
## Constant 8.041***
## (0.857)
##
## -----------------------------------------------
## Observations 187
## R2 0.304
## Adjusted R2 0.293
## Residual Std. Error 4.335 (df = 183)
## F Statistic 26.696*** (df = 3; 183)
## ===============================================
## Note: *p<0.1; **p<0.05; ***p<0.01
##
## Call:
## lm(formula = Loyalty * 100 ~ Tweets + Reactions + Episodes, data = Twitter.Project)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.1436 -3.1642 -0.1065 3.2228 10.5970
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 8.041e+00 8.566e-01 9.387 < 2e-16 ***
## Tweets -4.633e-06 1.875e-06 -2.470 0.014409 *
## Reactions 2.667e-05 7.314e-06 3.646 0.000347 ***
## Episodes 8.789e-02 4.671e-02 1.881 0.061512 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.335 on 183 degrees of freedom
## (24 observations deleted due to missingness)
## Multiple R-squared: 0.3044, Adjusted R-squared: 0.293
## F-statistic: 26.7 on 3 and 183 DF, p-value: 2.275e-14