shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. | Year | Membership 2013 2014 2015 2016 2017 2018 2019 2020 2021 17 16 16 21 20 20 23 25 24 (000s) (i) Use the following time scries data, to develop a regression equation relating memberships to time. (ii) Forecast 2023 membership.
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- Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs.Year 2013 2014 2015 2016 2017 2018 2019 2020 2021Membership (000s)17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time.Cinema HD an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction? What are the issues associated with qualitative forecasting, and how are these overcome? Provide an example of qualitative forecasting and explain the shortcomings.Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership 17 16 16 21 20 20 23 25 24 Use the following time series data, to develop a regression equation relating memberships to time. Forecast 2023 membership Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction?
- Question b. Movieflix, an online movie streaming service that offers a wide variety of award-winning TV shows, movies, animes, and documentaries, would like to determine the mathematical trend of memberships in order to project future needs. Year 2013 2014 2015 2016 2017 2018 2019 2020 2021 Membership (000s) 17 16 16 21 20 20 23 25 24 (i) Use the following time series data, to develop a regression equation relating memberships to time. (ii) Forecast 2023 membership. (iii) Assuming the COVID-19 pandemic comes to an end in 2021, in your opinion, how will this affect membership? Why? How will this affect your prediction?QUESTION 2 XXX Electric Illuminating Company is doing a survey on the relationship between electricity used in kilowatt-hours (thousand) and the number of rooms in a private single-family residence. A random sample of 10 homes was selected and the electricity consumption recorded as below. ii. Find a suitable linear regression equation ? = ? + ??. iii. Determine the number of kilowatt-hours (thousand) for an eleven-room residence.1) What is the probability of a stroke over the next 10 years for John Smith, a 68-year-old smoker who has blood pressure of 175? What action might the physician recommend for John to reduce the risk of stroke? 2) Is there any multicollinearity problem in the above multiple regression model? How do you know?
- Cascade Pharmaceuticals Company developed the following regression model, using time-series data from the past 33 quarters, for one of its nonprescription cold remedies: Y=−1.04+0.24X1−0.27X2�=−1.04+0.24�1−0.27�2 where Y� = quarterly sales (in thousands of cases) of the cold remedy X1�1 = Cascade's quarterly advertising (× $1,000) for the cold remedy X2�2 = competitors' advertising for similar products (× $10,000) Here is additional information concerning the regression model: sb1=0.042�b1=0.042, sb2=0.070�b2=0.070, R2=0.720�2=0.720, se=1.63��=1.63, F-statistic=31.402F-statistic=31.402, and Durbin-Watson (d) statistic=0.499Durbin-Watson (d) statistic=0.499. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy? (Hint: t0.05/2,33 - 3=2.042�0.05/2,33 - 3=2.042.) Check all that apply. X1�1 X2�2 What proportion of the total variation in sales is explained by the regression…Cascade Pharmaceuticals Company developed the following regression model, using time-series data from the past 33 quarters, for one of its nonprescription cold remedies:Y = -1:04 + 0:24X1 - 0:27X2where Y = quarterly sales (in thousands of cases) of the cold remedyX1 = Cascade’s quarterly advertising (× $1,000) for the cold remedyX2 = competitors’ advertising for similar products (× $10,000)Here is additional information concerning the regression model:sb1 = 0:032 sb2 = 0:070R2 = 0:64 se = 1:63 F-statistic = 31:402Durbin-Watson (d) statistic = 0.4995a. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy?b. What proportion of the total variation in sales is explained by the regression equation?c. Perform an F-test (at the 0.05 level) of the overall explanatory power of the model.d. What additional statistical information (if any) would you find useful in the evaluation of this model?The following scatterplot shows a company’s monthly sales, in thousands of dollars, versus monthly advertising dollars spent, in thousands of dollars. Which of the following points is most likely a high-leverage point with respect to a regression of monthly sales versus advertising dollars?
- The operations manager of a musical instrument distributor feels that the demand for Bass Drums may be related to the number of television appearances by the popular rick group Green Shades during the previous month. The manager has collected the data shown in the following table. Demand for Bass Drums 3 6 7 5 10 8 Green Shades TV appearances 3 4 7 6 8 5 Develop the linear regression equation to forecast. Forecast demand for Bass Drums when Green Shades’ TV appearances are 10. Compute MSE and standard deviation for Problem 8.It has been suggested that sales for the company may be connected to disposable income. Using the information below regarding historical disposable income, predict the sales for 2020 using regression analysis if a reliable prediction for disposable income for 2020 is $21,200. Year Disposable Income 2013 $18,000 2014 $18,618 2015 $19,099 2016 $24,453 2017 $24,906 2018 $20,388 2019 $21,425 Year Sales 2013 $225,000 2014 $193,000 2015 $248,000 2016 $300,000 2017 $340,000 2018 $295,000 2019 $310,000Discuss the cause of Heteroskedasticity in regression analysis