Hiya,

I'm a beginner at Studio and I'm feeling particularly low in confidence and would love some insight into how others would interpret this finding. The idea is to fit an appropriate intercept-only model predicting whether a respondent has felt depressed in the past week and then to state how does the intercept in this model represent the likelihood of having felt depressed.

With this output:

mod1 <- lm(formula = depressed ~ 1, data = dat)

summary(mod1)

Call:

lm(formula = depressed ~ 1, data = dat)

Residuals:

Min 1Q Median 3Q Max

-0.3655 -0.3655 -0.3655 0.6345 0.6345

##
Coefficients:

Estimate Std. Error t value Pr(>|t|)

(Intercept) 0.365506 0.008772 41.67 <2e-16 ***

Signif. codes: 0 ‘* ’ 0.001 ‘’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.4817 on 3014 degrees of freedom

My instinct is to answer:

"The intercept-only model predicts a 0.36 chance of a respondent reporting having felt depressed in the past week. Though the intercept is a small number, with a very small error margin and a high significance, it is worthy to consider the weight of the chance"

But I dont know why I feel like this is insufficient or even misguided, in that the 0.36 speaks to chance or percentage. Should anything else stand out to me in this output that could contribute to how understanding how the intercept represents likelihood of feeling depressed?

TIA