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 regression output given below. Coffee sales revenue 6.5010.005.504.503.5028.00 Temperature 25173035409 SUMMARY OUTPUT RegressionStatistios Multiple R RSquare Adjusted RSquare Standard Error Observations ANOVA Regression Residual Total Intercept Temperature 0.86440.74720.68405.20276df145 Coefficient 27.7179−0.6943SS320.0617108.27164283333 StandardError 5.66290.2019MS320.061727.0679 tStat 4.8946−3.4387F11.8244 P-value 0.00810.0263 Significance F0.0263 Lover 95% 11.9952−1.2549 Upper 95% 43.4406−0.1337 Test the significance of the slope, against a two-tailed alternative, at the 5% level of significance.
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