Description:
You are consultants working with local bakery chain. In order to better calibrate their models to predict sales, your supervisor has asked your group to develop a model to estimate the monthly sales of their bakeries based on survey data to create a 100 point scale of the quality of the local baked goods. A higher score indicates that the quality of the baked goods is higher.
You will use descriptive statistics, inferential statisticsand your knowledge of simple linear regression to complete this task.
Monthly salesdata for 25 locations (Dependent Variable)and number of competitors in the surrounding area(Independent Variable) are given in the Excel file: Data.xlsx.
Here is a table describing the variables in the data set:
Required:
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.
B. Draw a graph that displays the distribution of the quality of baked goods amongst the 25 stores.
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?
D. What is the likelihood that sales are more than $60,000when the quality is below a score of 60?Is salesgreater than $60,000 statistically independent of the event that the quality of baked goods is below a score of 60? Use a Contingency Table.
E. Estimate the 95% confidence interval for the population mean monthly sales.
F. Your supervisor recently stated that it is obvious that the mean monthly sales is greater than$45,000,which was the average monthly sales the previous month. Test his claim at the 10% level of significance.
G. Run a simple linear regression using the data and show the output from Excel.
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.
I. Is the sign of the coefficient what that you were expecting? Discuss.
J. Interpret the value of the R2.
Attachment:- data7-1.xlsx