Pop-Up Coffee Vendors Have Been Popular in the City of Adelaide

Essay

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) and number of different pastries and biscuits offered to customers 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 and number of different pastries and biscuits offered on that day, noted.
Excel output for a multiple linear regression is given below: $$\begin{array} { | c | c | r | } \hline \text { Coffee sales revenue } & \text { Temperature } & \text { Pastries/biscuits } \\\hline 6.5 & 25 & 7 \\\hline 10 & 17 & 13 \\\hline 5.5 & 30 & 5 \\\hline 4.5 & 35 & 6 \\\hline 3.5 & 40 & 3 \\\hline 28 & 9 & 15 \\\hline\end{array}$$ $\begin{array}{|l|r|r|r|r|r|c|}\hline \text { SUMMARV } \\\text { OUTPUT } \\\hline \text { Regression } \\\text { Stotistics } \\\hline \text { Multiple R } & 0.87 \\\hline \text { R Square } & 0.75 \\\hline \begin{array}{l}\text { Adjusted R } \\\text { Square }\end{array} & 0.59 \\\hline \text { Standard Error } & 5.95 \\\hline \text { Otservations } & 6.00 \\\hline\\\hline \text { ANOVA }\\\hline & & & & & \text { Significonce } \\& \text { df } & S S & M S & F & F \\\hline \text { Regression } & 2.00 & 322.14 & 161.07 & 4.55 & 0.12 \\\hline \text { Residual } & 3.00 & 106.20 & 35.40 \\\hline \text { Total } & 5.00 & 428.33 & \\\hline\\\hline & \text { Coefficients } & {\begin{array}{c}\text { Standard } \\\text { Error }\end{array}} & {\text { tStot }} & \text { Pvolue } & \text { Lower 95\% } & \begin{array}{c}\text { Upper } \\95 \%\end{array} \\\hline \text { Intercept } & 18.68 & 37.8 & 0.49 & 0.66 & -101.88 & 139.24 \\\hline \text { Temperature } & -0.50 & 0.83 & -0.60 & 0.59 & -3.15 & 2.15 \\\hline \text { Patries/bisouits } & 0.49 & 2.02 & 0.24 & 0.82 & -5.94 & 6.92 \\\hline\end{array}$ Interpret the intercept. Does this make sense?