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11332 Management

Question

Task:   This assignment has two parts. Part 1 has questions about forecasting, covered in unit 5. You will submit your answers to part 1 using the Unit 6 Assignment template located in Course Documents. You still need to submit the Excel file you used to generate your answers, in addition to the report in Word. Part 2 covers content from units 1-4 and requires you to analyze a case. For this, you will prepare a PowerPoint presentation to present your findings. See further instructions below under “Part 2-Case Analysis” for more details.  Question 1  A store managers wishes to forecast the weekly number of television sets sold. Calculate the error for each of the following forecasts, the MAD and the MSE. Be sure to show the entire table in the work area of the template.
Question 2  The data below shows the number of goods manufactured in one year. (\$ billion). Calculate forecasts for years 6 through 13 using a 5-year moving average.  Then, calculate forecasts for years 6 through 13 using a 5-year weighted moving average. Weight the most recent year by 6, the previous year by 4, the year before that by 2, and the other years by 1. Be sure to show the entire table in the work area of the template. Answer the following questions
:  a)What is the forecast for year 13 based on the 5-year moving average?
b)What is the forecast for year 13 based on the 5-year weighted moving average?
c)What is the MAD for the moving average forecast?
d)What is the MAD for the weighted moving average forecast? e)Which forecasting model that you calculated is better? Why?
a.What is the average rating for all CBC movies? How about ABN movies and BBS movies?
b.Include a table that shows the average and the other descriptive statistics (using the data analysis tool pack in Excel) for the ratings of the three networks (one column for each network). Explain what you learn from each of the metrics in the table.
c.Comment how the networks are performing, using the metrics in the table. Your analysis should extend beyond simply comparing the average ratings for each network.
2.Create a line graph of the monthly average ratings for CBC for the year. Note that there are multiple ratings data for the months; you will need to calculate an average for each month first, and then plot the averages. After you create the graph, fit a linear trend line, displaying the formula and the r-squared. Explain to the executives if you can use this time series data to forecast the ratings of upcoming months. How accurate can you expect this forecast to be?
3.Should the CBC hire stars for their movies? To answer this question, run a hypothesis test to see if there is a significant difference between the ratings of movies with stars versus movies without stars. Use the data for CBC movies only. Use 95% confidence.  Answer the following:
a.What are the null and alternative hypotheses (state in full sentences)?
b.Run the test using Excel and include the output table. Use a t-test assuming equal variances.
4.Run a multiple regression where the dependent variable is ratings and the independent variables are star and fact. Use data from CBC only. CBC Management has several questions:
a.Which dependent variable contributes more when determining a movie’s rating: Being fact-based or having one star? How much does each of these factors change the ratings?
b.How well does this regression analysis explain the ratings? Justify your answers referring to the relevant figures.
c.Are either, both, or neither of the independent variables significantly related to the ratings at 95% confidence? Justify your answers referring to the relevant figures.

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