df SS MS F Significance F Regression 2 3907.938 1953.969 19.043 0.000 Residual 10 1026.062 102.606 Total 12 4934 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 87.764 17.263 5.084 0.000 49.300 126.229 Opening times (hours) 0.923 0.191 4.840 0.001 0.498 1.348 Temperature (degrees 0.254 0.592 0.429 0.677 -1.065 1.573 a) Interpret the coefficient of opening times. b) Using the 5% significance level, test whether this is a significant linear relationship between electricity bill and opening times; give hypotheses, your reasoning, decision and conclusion.The owner of a store wants to investigate the multiple linear regression between annual electricity bill ($000) with store opening times (hours) and the temperature outside (degrees Celsius) . A random sample was taken (given below), and Excel was used to create the following multiple linear regression output. Electricity bill ($000) Opening times (hours) Temperature (degrees Celsius) 134 51 30 123 40 45 178 90 40 156 55 35 145 45 30 178 90 42 156 55 34 134 50 30 167 60 38 156 50 35 134 50 30 124 40 24 178 90 40 SUMMARY OUTPUT Regression Statistics Multiple R 0.890 R Square 0.792 Adjusted R Square 0.750 Standard Error 10.129 Observations 13 ANOVA