In: Statistics and Probability
You have been asked to engage in one final project for the chain of department stores for which you have been working concerning the sales of a type of shirt that they carry. Specifically, this time you wish to study the nature of the relationship between the average daily number of hours the stores are open and monthly sales for the month you have been studying. You wish to utilize the average daily number of hours the stores are open as a variable designed to predict and explain sales of the item in this month. Data concerning these two variables of interest is collected from a random sample of stores throughout the chain of stores. This data is shown on the next page. Various questions will be asked and then need to be answered about the results you generate. These questions follow the presentation of the data. You should answer the questions posed in a memo that will accompany your results. Where appropriate, be sure to annotate the printouts you include as a part of the work you have accomplished.
Data: Number of Hours Sales
14 348
12 355
9 325
10 401
22 455
20 398
18 288
17 350
13 380
19 438
18 386
23 430
19 320
20 489
11 354
22 480
17 420
19 456
9 289
15 376
13 337
11 306
f) Find the sample coefficient of determination for the above data. Explain its meaning relative to the problem.
g) Find the adjusted sample coefficient of determination for the above data. Explain its meaning relative to the problem. Why does it differ, if it does, from the coefficient of determination that you found in the previous part of the problem?
h) Find the sample standard error of the estimate for the above data. Explain its meaning relative to the problem.
i) Find the sample coefficient of correlation for the above data. Explain its meaning relative to the problem.
j) Perform a complete residual analysis on this sample data to decide of the method of least squares is an appropriate way to analyze the data of this model. Be sure to address all aspects of a good residual analysis. Be sure to provide all the necessary printouts to do this. Include a check for the presence of autocorrelation at the 1% level of significance.
Hint: dL = 1.00 and dU = 1.17
Answer to the
question)
Enter the data in excel
Click Data tab
Click on regression
click ok
the regression window shows up:
.
Input Y range as sales data
Input X range as hours data
tick mark the check box next to labels
Tick mark for residuals and residual plots
Click OK
The following output appears on screen:
.Answer f: coefficient of determination = R square = 0.43032
Answer g: adjusted value = 0.40183
Answer h : standard error = 46.3626
Answer i: Coefficient of correlation = 0.65599