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Course 2022 Fall Graduate Foundations of Data Analytics (ANA-500-F22A, ANA-500- F22C) Test Module 04 Week 7 gretl Assignment Started 10/9/22 8:57 PM Submitted 10/9/22 9:06 PM Due Date 10/9/22 11:59 PM Status Completed Attempt Score 66 out of 100 points Time Elapsed 8 minutes Instructions The online portion of this gretl assignment has a variety of types of questions; multiple choice, fill in the blank, true/false, etc. Please select the choice that best answers the question or enter a value rounded to two decimal places unless otherwise instructed. If you have any questions just ask! If you didn't already download it, here is a copy of the Word document associated with this week's assignment. Module 4 Week 1, gretl 7 ANA 500.docx  Question 1 4 out of 4 points Considering the descriptive statistics for the cafeteria.gdt data, this dataset does NOT have sufficient observations (or records) to build an OLS model without worry about sample size. Therefore, we will have to modify the distributions used for tests of the model to compensate.  Question 2 4 out of 4 points Thinking about consistent units and the listed units for sales, price and advertising costs

(adv_cost), an adjustment may need to be made to values in price for a direct comparison to the other variables sales (revenue) and advertising cost (adv_cost).  Question 3 5 out of 5 points The simple linear regression model for this situation is: (Hint: remember the definition of simple linear regression, multivariable linear regression, multivariate regression and so on!)  Question 4 4 out of 4 points I have included tests for normality, linearity, and homoscedasticity in the script at the end of this Word doc. You can read more specifics about them in the output from the gretl script as well as in the various manuals and command help files available for gretl. Using the data in the data file cafeteria.csv, consider the descriptive statistics, frequencies, and develop a simple linear model to represent these data. The assumption of normality is satisfied.  Question 5 5 out of 5 points I have included tests for normality, linearity, and homoscedasticity in the script at the end of

this Word doc. You can read more specifics about them in the output from the gretl script as well as in the various manuals and command help files available for gretl. Using the data in the data file cafeteria.csv, consider the descriptive statistics, frequencies, and develop a simple linear model to represent these data. The assumption of linearity is satisfied.  Question 6 5 out of 5 points I have included tests for normality, linearity, and homoscedasticity in the script at the end of this Word doc. You can read more specifics about them in the output from the gretl script as well as in the various manuals and command help files available for gretl. Using the data in the data file cafeteria.csv, consider the descriptive statistics, frequencies, and develop a simple linear model to represent these data. The assumption of homogeneity or homoscedasticity is satisfied.  Question 7 0 out of 5 points Analyze the coefficients related to the explanatory (independent) variables.  Question 8 5 out of 5 points

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The value of the intercept of the regression line is _________.  Question 9 6 out of 6 points The coefficient of price is _________.  Question 10 4 out of 4 points The coefficient of adv_cost is _________.  Question 11 0 out of 4 points How much annual revenue will be generated if the average price per meal is $5.50 and the advertising costs are capped at $1,200? In this case, be sure to round correctly to the dollar (USD). (Hint: you’ve done this before when considering other variables and ensuring you are using consistent units, i.e. remember that the problem statement says that values are in 1,000’s of dollars (USD).)  Question 12 0 out of 4 points Determine the number of degrees of freedom for this problem. (Hint: remember the formula where N is the number of observations and K is the number of unknown coefficients.)

The number of degrees of freedom is _________.  Question 13 0 out of 5 points The 95% confidence interval for price has a lower limit of _________ and,  Question 14 0 out of 4 points the 95% confidence interval for price has an upper limit of __________ .  Question 15 0 out of 4 points Based on the computed 95% confidence interval this means that if the price per meal is “decreased” by 10 cents or 0.10 that means that sales (revenue) would be increased by between _______ and,... (Hint: remember that the units are 1,000’s of dollars (USD).)  Question 16 0 out of 4 points Continued from Q12a:

an upper limit of __________. (Hint: remember that the units are 1,000’s of dollars (USD).)  Question 17 4 out of 4 points The computed t-statistic (or t-ratio) for price is __________. (See attached Word doc for the rest of the text of this question!)  Question 18 4 out of 4 points Using the same hypothesis test or computing with gretl, the t-ratio for the advertising costs (adv_cost) is ________ .  Question 19 4 out of 4 points These values are the same as the values computed and included in the table for the original OLS model.  Question 20 4 out of 4 points The corresponding P-values indicate that we must reject the null hypothesis, i.e. the P-value is much less than 0.05. Therefore, both price and adv_cost are significant variables and

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should be included in the model.  Question 21 4 out of 4 points The null and alternate hypotheses to test if any additional dollars of advertising will generate additional sales is:  Question 22 0 out of 4 points Assume a level of significance of and find the relevant critical value. Treat the null hypothesis as an equality, i.e. is _________.  Question 23 4 out of 4 points Compute any additional required values to determine whether or not there is sufficient evidence to confirm that additional dollars spent on advertising will be cost effective, i.e. result in increased sales (revenue). Answer the question, “There is sufficient evidence to confirm that additional money spent on advertising will result in increased revenue.” Yes or No.

Sunday, October 9, 2022 9:06:19 PM EDT