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Trust 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. month t 1 2 3 4 5 6 7 8 9 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 Exponential Smoothing method is: 2. What should be the preferred method for forecasting here? 3. The predicted value for October (19h month) new accounts = ,

Trust 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. month t 1 2 3 4 5 6 7 8 9 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 Exponential Smoothing method is: 2. What should be the preferred method for forecasting here? 3. The predicted value for October (19h month) new accounts = ,

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)
6th Edition
ISBN:9781337111348
Author:Bruce Crauder, Benny Evans, Alan Noell
Publisher:Bruce Crauder, Benny Evans, Alan Noell
Chapter5: A Survey Of Other Common Functions
Section5.3: Modeling Data With Power Functions
Problem 6E: Urban Travel Times Population of cities and driving times are related, as shown in the accompanying...
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Trust 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. month t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 new Yt 200 225 235 240 245 265 280 265 290 285 270300 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 Exponential Smoothing method is: 2. What should be the preferred method for forecasting here? 3. The predicted value for October (19th month) new accounts =
Transcribed Image Text:Trust 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. month t 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 new Yt 200 225 235 240 245 265 280 265 290 285 270300 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 Exponential Smoothing method is: 2. What should be the preferred method for forecasting here? 3. The predicted value for October (19th month) new accounts =
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