Chapter 1. Truist Bank started its operations in April 2020. Since then, they have collected monthly data regarding new accounts opened in the bank every month until September 2021. The table below shows how the new accounts for each of those 18 months. Imonth t 1 2 3 4 5 6 7 18 19 10 11 12 13 14 15 16 17 18 new Yt 200 225 235 240 245 265 280 265 290 285 270 300 305 310 320 340 360 365 accounts Based on this information, they would like to predict how many new accounts they can expect to get in the month of October (the 19th month). However, there is a disagreement among their managers on which of the following methods is the most suitable for making the predictions: • Regression Analysis (with no seasonality) • Moving Average (with m = 3) • Exponential smoothing (with alpha = 0.33) Do a comparison analysis by finding the MSES using all three methods and fill in the blanks below (round to two decimal places): 1. The MSE obtained using the Regression Analysis model is: 2. The MSE obtained using the Moving Average method is: 3. The MSE obtained using the Exponential Smoothing method is: 4. What should be the preferred method for forecasting here? : 5. The predicted value for October (19th month) new accounts =

Linear Algebra: A Modern Introduction
4th Edition
ISBN:9781285463247
Author:David Poole
Publisher:David Poole
Chapter2: Systems Of Linear Equations
Section2.4: Applications
Problem 28EQ
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Chapter 1. Truist Bank started its operations in April 2020. Since then, they have collected monthly data regarding new accounts opened in the bank every month until September
2021. The table below shows how the new accounts for each of those 18 months.
t 1
|4 5 6 7
month
2
8
10 11 12 13 14 15 16 17 18
new
Yt 200 225 235 240 245 265 280 265 290 285 270 300 305 310 320 340 360 365
accounts
Based on this information, they would like to predict how many new accounts they can expect to get in the month of October (the 19th month). However, there is a disagreement
among their managers on which of the following methods is the most suitable for making the predictions:
• Regression Analysis (with no seasonality)
Moving Average (with m = 3)
• Exponential smoothing (with alpha = 0.33)
Do a comparison analysis by finding the MSES using all three methods and fill in the blanks below (round to two decimal places):
1. The MSE obtained using the Regression Analysis model is:
2. The MSE obtained using the Moving Average method is:
3. The MSE obtained using the Exponential Smoothing method is:
4. What should be the preferred method for forecasting here? :
5. The predicted value for October (19th month) new accounts =
Transcribed Image Text:Chapter 1. Truist Bank started its operations in April 2020. Since then, they have collected monthly data regarding new accounts opened in the bank every month until September 2021. The table below shows how the new accounts for each of those 18 months. t 1 |4 5 6 7 month 2 8 10 11 12 13 14 15 16 17 18 new Yt 200 225 235 240 245 265 280 265 290 285 270 300 305 310 320 340 360 365 accounts Based on this information, they would like to predict how many new accounts they can expect to get in the month of October (the 19th month). However, there is a disagreement among their managers on which of the following methods is the most suitable for making the predictions: • Regression Analysis (with no seasonality) Moving Average (with m = 3) • Exponential smoothing (with alpha = 0.33) Do a comparison analysis by finding the MSES using all three methods and fill in the blanks below (round to two decimal places): 1. The MSE obtained using the Regression Analysis model is: 2. The MSE obtained using the Moving Average method is: 3. The MSE obtained using the Exponential Smoothing method is: 4. What should be the preferred method for forecasting here? : 5. The predicted value for October (19th month) new accounts =
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