In Section 12.4, we presented a formula for Vsb0 1 b1x*dand a CI for b0 1 b1x*. Taking
Chapter 12, Problem 78(choose chapter or problem)
In Section 12.4, we presented a formula for \(V\left(\hat{\beta}_{0}+\hat{\beta}_{1} x^{*}\right)\) and a CI for \(\beta_{0}+\beta_{1} x^{*}\). Taking x* = 0 gives \(\sigma_{\hat{\beta}_{0}}^{2}\) and a CI for \(\beta_{0}\). Use the data of Example 12.11 to calculate the estimated standard deviation of \(\hat{\beta}_{0}\) and a 95% CI for the y-intercept of the true regression line.
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