Homework Help is Here – Start Your Trial Now!
Math
Statistics
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 =

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 =

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
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 =
Expert Solution
trending now

Trending now

This is a popular solution!

steps

Step by step

Solved in 4 steps with 3 images

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Similar questions
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS