Reference no: EM133280427
Question 1: Stanley Cup Ring Auction Price Prediction:
Jack has collected the data of several Stanley Cup rings sold in the Hockey Memorabilia auctions in the past year and plans to use the data to predict the average selling prices of similar items in the upcoming auction. The data includes final auction selling price, weight, and type of metal (10K Gold, 14K Gold or Sterling Silver), as well as whether each ring had diamonds or not.
Help Jack to construct a multiple regression model for this problem. (Hint: Create a set of binary independent variables to represent the metal types, and another independent variable for the diamond). Provide the mathematical equation of the regression model, and then perform the regression analysis in Excel.
What is the estimated regression function?
Interpret the value of R2 for this model.
Write down the hypothesis test for the overall significance of this model (write the null and alternative hypotheses). What are the degrees of freedom in the overall F test?
What is p-value of the overall F test? (Hint: use Excel's regression report). Assuming α = 0.05, How would you use p-value to decide whether to reject the null hypothesis or not?
What other variables do you think Jack could consider including in the model to help improve the model?
Question 2: PlotYacht - A Luxury Yacht Manufacturing Company
PlotYacht was established in 2018. Excel file "HW3.xlsx" shows the sales quantities of the LuckYacht model, a semi-luxury yacht, which entered the market in 2019. The manufacturer hopes to forecast the demand of LuckYacht for each quarters of 2022 using the historical data collected in years 2019 to 2021. Help the manufacturer forecast the demands, given the parameters in the Excel template file, using
moving averages method with n1
moving averages method with n2
exponential smoothing method with α1
exponential smoothing method with α2
linear trend analysis with and without the presence of seasonality assumption.
Plot the actual sales and the forecasts in each of the forecast models in (a) to (e) using Scatterplot. Feel free to combine some of them too if you want to compare the forecasts visually.
Compute the forecast error measures (all three discussed in class) and recommend which forecasting method the manufacturer should go with, based on those measures.
Which forecast is better between the two moving averages approaches? Why is this the case (provide explanations other than comparing the error measure values)?
Which forecast is better between the two exponential smoothing approaches? Why is this the case (provide explanations other than comparing the error measure values)?
Which forecasting model better explains and predicts the demand pattern overall? Why is this the case (provide explanations other than comparing the error measure values)?
Think about a couple of years from now (say 2025). Do you think the best forecasting model you obtained here would still be a proper model to use, even if you included the new data from 2021 to say 2024? Why? (hint: the company is established in 2018). What could happen to the pattern of sales over time. Discuss.
Note that you will need to enter your Student Number in the template to obtain the parameters assigned to your problem. Read the instructions in the Excel file and follow them carefully, especially α values, and see whether the numbers given to you are α or 1 - α. Use the template file, but feel free to use different Excel sheets for your models.
Attachment:- Stanley Cup Ring Auction Price Prediction.rar