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|r|r|r|r|c|}\hline \begin{array}{l}\text { SUMMARY } \\\text { OUTPUT }\end{array} \\\hline \begin{array}{c}\text { Regression } \\\text { Stotistics }\end{array} \\\hline \text { Multiple R } & 0.8644 \\\hline \text { RSquare } & 0.7472 \\\hline \text { Adjusted R Square } & 0.6840 \\\hline \text { Stan dard Error } & 5.2027 \\\hline \text { Observations } & 6 \\\hline\\\hline \text { ANOVA }\\\hline & & & & & \text { Significance } \\& \text { df } & S & M S & F &{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 & 428.3333 & & & \\\hline\\\hline & \text { Coefficients } & \begin{array}{c}\text { Standord } \\\text { Error }\end{array} & \text { t Stat } & \text { p-value } & \text { Lower 95\% } & \begin{array}{c}\text { Upper } \\95 \%\end{array} \\\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.

The Manager of a Fast Food Restaurant Wants to Determine

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