Isabella is a retailer who wants to test a theory about retail turnover in NSW. She downloads NSW estimated resident population data (in thousands) for each quarter from March 1990 to December 2015 and the corresponding seasonally adjusted retail turnover figures for NSW (in $million) from the Australian Bureau of Statistics (Australian Economic Indicators, July 2016 and Australian Demographic Statistics, June 2016) and runs a regression analysis. The output for this is shown below

1. How well does the regression line fit the observed data? Explain.
2. What is the sample correlation coefficient between the two variables in this model and how can it be interpreted?
3. Write the sample regression equation clearly defining the variables used.
4. In a way that Isabella's staff could understand, interpret this equation to explain the estimated retail expenditure in September quarter 2012 when there were 7,000,707 residents of NSW, and the rate of increase thereafter.

SUMMARY OUTPUT Regression Statistics Multiple R 0.98883578 R Square 0.9777962 Adjusted R Square 0.97757852 Standard Error 494.743053 Observations 104 ANOVA Df SS MS F Significance F Regression 1 1099463224 1.1E+09 4491.809 3.70804E-86 Residual 102 24966610.26 244770.7 Total 103 1124429834 Standard Coefficients Error t Stat P-value Lower 95% Upper 95% Intercept 29215.132 636.882281 -45.8721 6.59E-70 -30478.38548 -27951.88 Resident Population 6.66888805 0.099504513 67.02096 3.71E-86 6.471521318 6.86625478