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A Confidence Interval for The yy -Intercept β0\beta _ { 0 }

question 113

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A confidence interval for the yy -intercept β0\beta _ { 0 } for a regression line y=β0+β1xy = \beta _ { 0 } + \beta _ { 1 } x can be found by evaluating the limits in the interval below:
b0E<β0<b0+E,\mathrm { b } _ { 0 } - \mathrm { E } < \beta _ { 0 } < \mathrm { b } _ { 0 } + \mathrm { E } ,
where E=(tα/2) se1n+x2/[x2(x) 2/n]\mathrm { E } = \left( \mathrm { t } _ { \alpha / 2 } \right) \mathrm { se } \sqrt { \frac { 1 } { \mathrm { n } } + \overline { \mathrm { x } } 2 / \left[ \sum \mathrm { x } ^ { 2 } - \left( \sum \mathrm { x } \right) ^ { 2 } / \mathrm { n } \right] } .
The critical value tα/2t _ { \alpha / 2 } is found from the tt -table using n2n - 2 degrees of freedom and b0b _ { 0 } is calculated in the usual v from the sample data.
Use the data below to obtain a 95%95 \% confidence interval estimate of β0\beta _ { 0 } .
x (hours studied)  2.54.55.17.911.6y (score on test)  6670608393\begin{array}{c|ccccc}\mathrm{x} \text { (hours studied) } & 2.5 & 4.5 & 5.1 & 7.9 & 11.6 \\\hline \mathrm{y} \text { (score on test) } & 66 & 70 & 60 & 83 & 93\end{array}


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