The slope is how much y is predicted to change for each one-unit increase in x. A slope of 4.08 means each 1-unit increase in x is associated with a predicted 4.08-unit increase in y. A negative slope means y decreases as x increases.
Should I trust a prediction far outside my data range?+−
No — predicting outside the range of x values you actually observed is called extrapolation, and it's risky. There's no evidence the same straight-line relationship continues to hold beyond the data that built the model. Only trust predictions within, or close to, your observed range.
What does R² mean here?+−
R² is the proportion of variance in y explained by the linear relationship with x, from 0 to 1. An R² of 0.85 means 85% of the variation in y is associated with variation in x. For simple linear regression, R² equals the square of the Pearson correlation coefficient.
Does a good fit mean a straight line was the right choice?+−
Not necessarily — R² measures how tightly points cluster around the fitted line, not whether a line was the right shape to fit in the first place. Always look at the scatter plot; a curved relationship can still produce a deceptively high R² if not checked visually.