Pop-up coffee vendors have been popular in the city of Adelaide in 2013. A vendor is interested in knowing how temperature (in degrees Celsius) impacts daily hot coffee sales revenue (in $00's).
A random sample of 6 days was taken, with the daily hot coffee sales revenue and the corresponding temperature of that day noted. Excel output given below.

\begin{array} { | c | c | } \hline \text { Coffee sales revenue } & \text { Temperature } \\\hline 6.50 & 25 \\\hline 10.00 & 17 \\\hline 5.50 & 30 \\\hline 4.50 & 35 \\\hline 3.50 & 40 \\\hline 28.00 & 9 \\\hline\end{array}

\begin{array}{|l|r|c|c|c|r|r|}\hline \text { SUMMARY OUTPUT } & & \\\hline \text { RegressionStatistios } & & \\\hline \text { Multiple R } & 0.8644 & \\\hline \text { RSquare } & 0.7472 & \\\hline \text { Adjusted RSquare } & 0.6840 & \\\hline \text { Standard Error } & 5.2027 & \\\hline \text { Observations } & 6 & \\\hline\\\hline \text { ANOVA } & & & & & & \\\hline & d f & S S & M S & F & \text { Significance } F & \\\hline \text { Regression } & 1 & 320.0617 & 320.0617 & 11.8244 & 0.0263 & \\\hline \text { Residual } & 4 & 108.2716 & 27.0679 & & & \\\hline \text { Total } & 5 & 4283333 & & & & \\\hline\\\hline & \text { Coefficient } & \text { StandardError } &{\text { tStat }} & \text { P-value } & \text { Lover 95\% } & {\text { Upper 95\% }} \\\hline \text { Intercept } & 27.7179 & 5.6629 & 4.8946 & 0.0081 & 11.9952 & 43.4406 \\\hline \text { Temperature } & -0.6943 & 0.2019 & -3.4387 & 0.0263 & -1.2549 & -0.1337 \\\hline\end{array}

Test the hypothesis that the population intercept is positive, at the 5% level of significance.

In a Regression Problem, If the Coefficient of Determination Is

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