Referencing Styles : Harvard A. Calculate the descriptive statistics from the data and display in a table. Be sure to comment on the central tendency, variability (both absolute and relative) as well as shape for each variable. (1 Mark) B. Draw a graph that displays the distribution of the distance of the stores to the centre of Singapore. (1 Mark) C. Create a box-and-whisker plot for the distribution of monthly sales and describe the shape. Is there evidence of outliers in the data? (1 Mark) D. What is the likelihood that sales are more than $60,000 and more than 4 kilometres from the centre of the city? Is sales statistically independent of distance? Use a Contingency Table. (2 Marks) E. Estimate the 90% confidence interval for the population mean monthly sales. (1 Mark) F. Your supervisor recently stated that it is obvious that the mean monthly sales is greater than $40,000, which was the average monthly sales the previous month. Test his claim at the 5% level of significance. (1 Mark) G. Run a simple linear regression using the data and show the output from Excel. (1 Mark) H. Is the coefficient estimate for the slope statistically different than zero at the 5% level of significance? Set-up the correct hypothesis test using the results found in the table in Part (G) using both the critical value and p-value approach. Interpret the coefficient estimate of the slope. (2 Marks) I. Is the sign of the coefficient what that you were expecting? Discuss. (1 Mark) J. Interpret the value of the R2. (1 Mark) K. What is the predicted monthly sales of a store that is 5 kilometres away from the city centre? Discuss whether it is appropriate to use the regression results to predict monthly sales for stores further than 10 kilometres away. (1 mark) L. Do the results suggest that the data satisfy the assumptions of a linear regression: Linearity, Normality of the Errors, and Homoscedasticity of Errors? Show using scatter diagrams, normal probability plots and/or histograms and Explain. (3 Marks) M. Based on the results of the regressions, is it likely that other factors have influenced monthly sales? If so, provide a couple possible examples and indicate whether these would likely influence the regression results if they were included. (1 Mark) N. If a community housing organisation asked for information regarding the characteristics of housing targeting the households of Chinese, explain whether a simple random sampling technique would provide an accurate representation of these households. (Note: This question does not use the data)