The image shows a statistical summary from a linear regression model, run in R, and asks which number represents the regression coefficient $\beta$ estimate for the variable $x$. Let me help interpret the summary.

The regression coefficient $\beta$ is listed under the Coefficients section of the output, corresponding to $x$.

Looking at the output:

• The estimate for $x$ is 2.7587 (second row under "Estimate").

Thus, the correct choice for $\beta$-estimate is b. 2.7587.

Would you like a detailed explanation about regression output interpretation or have any further questions?

Here are five related questions to expand your understanding:

1. What does the $p$-value associated with $x$ indicate in this model?
2. How is the Adjusted $R^2$ different from the Multiple $R^2$?
3. What is the significance of the residual standard error in the summary?
4. How do you interpret the $F$-statistic value and its $p$-value?
5. What is the purpose of the intercept in a regression model?

Tip: Always check the $p$-value for coefficients to determine their statistical significance!