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: Coffee sales revenue 6.5105.54.53.528 Temperature 25173035409 Pastries/biscuits 71356315 SUMMARV OUTPUT Regression Stotistics Multiple R R Square Adjusted R Square Standard Error Otservations ANOVA Regression Residual Total Intercept Temperature Patries/bisouits 0.870.750.595.956.00 df 2.003.005.00 Coefficients 18.68−0.500.49SS322.14106.20428.33 Standard Error 37.80.832.02MS161.0735.40 tStot 0.49−0.600.24F4.55 Pvolue 0.660.590.82 Significonce F0.12 Lower 95% −101.88−3.15−5.94 Upper 95%139.242.156.92 Comment on the difference between the coefficient of determination and the Adjusted coefficient of determination.
Apply the concept of allowance for doubtful accounts and bad debts expense in accounting practices.
Comprehend the impact of uncollectible accounts on financial statements.
Prepare journal entries for estimating and adjusting allowance for doubtful accounts.
Recognize the presentation of allowance for doubtful accounts on the balance sheet.
Social Planning
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