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

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Essay

Pop-up coffee vendors have been popular in the city of Adelaide in 2013. A Pop-up coffee 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:  Coffee sales revenue  Temperature  Pastries/biscuits 6.52571017135.53054.53563.540328915\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}  SUMMARY OUTPUT  Regression Statistios  Multiple R 0.87 R Square 0.75 Adjusted R Square 0.59 Standard Error 5.95 Observations 6.00 ANOVA dfSSMSF Significance F Regression 2.00322.14161.074.550.12 Residual 3.00106.2035.40 Total 5.00428.33 Coeffients  Standard Error  tStat  P-value  Lower 95% Upper 95% Intercept 18.6837.880.490.66101.88139.24 Temperature 0.500.830.600.593.152.15 Pastries/biscuits 0.492.020.240.825.946.92\begin{array}{|l|r|l|l|l|l|l|}\hline \text { SUMMARY OUTPUT } & & & & & & \\\hline \text { Regression Statistios } & & & & & & \\\hline \text { Multiple R } & 0.87 & & & & & \\\hline \text { R Square } & 0.75 & & & & & \\\hline \text { Adjusted R Square } & 0.59 & & & & & \\\hline \text { Standard Error } & 5.95 & & & & & \\\hline \text { Observations } & 6.00 & & & & & \\\hline \\\hline \text { ANOVA } & & & & & \\\hline & {d f} & SS & M S & F & \text { Significance } 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 { Coeffients } & \text { Standard Error } & \text { tStat } & \text { P-value } & {\text { Lower } 95 \%} & {\text { Upper } 95 \%} \\\hline \text { Intercept } & 18.68 & 37.88 & 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 { Pastries/biscuits } & 0.49 & 2.02 & 0.24 & 0.82 & -5.94 & 6.92 \\\hline\end{array} a. Write down the multiple regression model.
b. Interpret the coefficient of Temperature.
c. Interpret the coefficient of Pastries/biscuits.


Definitions:

Title

Legal ownership of property, especially real estate or automobiles.

Oral Contracts

Agreements that are made verbally and are legally binding, though harder to prove than written contracts.

Written Confirmation

A document that records and verifies specific details of an agreement or transaction between two or more parties.

Merchant

An individual or company engaged in the wholesale purchase and retail sale of goods for profit.

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