(a) Compute four-week and five-week moving averages for the time series. Do not round intermediate calculations. If required, round your answers to two decimal places. Week Sales 4-Week Moving Average 5-Week Moving Average 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 (b) Compute the MSE for the four-week and five-week moving average forecasts. Do not round intermediate calculations. If required, round your answers to two decimal places. MSE for four-week moving average = MSE for five-week moving average = Refer to the gasoline sales time series data in the given table. Click on the datafile logo to reference the data. DATA file Week Sales (1,000s of gallons) 1 17 2 21 3 19 4 23 5 6 7 18 16 8 20 18 6 22 10 20 11 15 12 22

(a) Compute four-week and five-week moving averages for the time series. Do not round intermediate calculations. If required, round your answers to two decimal places. Week Sales 4-Week Moving Average 5-Week Moving Average 1 17 2 21 3 19 4 23 5 18 6 16 7 20 8 18 9 22 10 20 11 15 12 22 (b) Compute the MSE for the four-week and five-week moving average forecasts. Do not round intermediate calculations. If required, round your answers to two decimal places. MSE for four-week moving average = MSE for five-week moving average = Refer to the gasoline sales time series data in the given table. Click on the datafile logo to reference the data. DATA file Week Sales (1,000s of gallons) 1 17 2 21 3 19 4 23 5 6 7 18 16 8 20 18 6 22 10 20 11 15 12 22

Essentials Of Business Analytics

1st Edition

ISBN:9781285187273

Author:Camm, Jeff.

Publisher:Camm, Jeff.

Chapter5: Time Series Analysis And Forecasting

Section: Chapter Questions

Problem 7P

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Similar questions

During computation, you may round your integer data to two decimal places and your percentages and present value factors to four decimal places.
Consider the following time series: a. Construct a time series plot. What type of pattern exists in the data? Is there an indication of a seasonal pattern? b. Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2, 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year.
Consider the following time series data: Compute MSE using the most recent value as the forecast for the next period. What is the forecast for month 8? Compute MSE using the average of all the data available as the forecast for the next period. What is the forecast for month 8? Which method appears to provide the better forecast?
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Use a multiple regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Qtr1 = 1 if quarter 1, 0 otherwise; Qtr2 = 1 if quarter 2. 0 otherwise; Qtr3 = 1 if quarter 3, 0 otherwise. Compute the quarterly forecasts for next year based on the model you developed in part (b). Use a multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part (b) to capture seasonal effects and create a variable t such that t = 1 for quarter 1 in year 1, t = 2 for quarter 2 in year 1, … t = 12 for quarter 4 in year 3. Compute the quarterly forecasts for next year based on the model you developed in part (d). Is the model you developed in part (b) or the model you developed in part (d) more effective? Justify your answer.
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 8. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 8. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
Consider the following time series data: Construct a time series plot. What type of pattern exists in the data? Develop a three-week moving average for this time series. Compute MSE and a forecast for week 7. Use α = 0.2 to compute the exponential smoothing values for the time series. Compute MSE and a forecast for week 7. Compare the three-week moving average forecast with the exponential smoothing forecast using α = 0.2. Which appears to provide the better forecast based on MSE? Explain. Use trial and error to find a value of the exponential smoothing coefficient α that results in a smaller MSE than what you calculated for α = 0.2.
The aging of Torme Designs shown below. Calculate the amount of each periodicity range that is deemed to be uncollectible. The Allowance for Doubtful Accounts carries a credit balance of $1,135.00. Write the adjusting entry for the end of the current year. Est Uncollectible Accts Age Interval: Balance: Percentage: Amount: Not past due 850,000 3.50% 1~30 days past due: 47,500 5.00% 31~60 days past due: 21,750 10.00% 61~90 days past due: 11,250 20.00% 91~180 days past due: 5,065 30.00% 181~365 days past due: 2,500 50.00% Over 365 days past due: 1,145 95.00% Total: 939,210
You tested the allowance for uncollectible accounts with regression analysis, and obtained the following results: MAXIMUM TOLERABLE MISSTATEMENT = $500 $0 $500 $750 $1,500 LCL ALLOW UCL THIS IS THE ALLOWANCE CURRENTLY RECOGNIZED, $750 By what amount should the currently recognized allowance, $750, be credited so that the adjusted allowance is materially correct? $250 $0 $500 $750
b. Prepare a vertical analysis of the segment data. Round all percents to one decimal place and round the total percentage to 100 if necessary.
In cell F5, insert a lookup function that uses the credit rating to determine the minimum down payment based on the table array A:15:c:18. Include the range_lookup argument to ensure an exact match. Multiply the function result by the negotiated cost of the vehicle.
Please Download EURUSD spot exchange rate data from Yahoo Finance by using ‘yfinance’ module or use FRED database (from website or API connection). Data period: 2010-Jan to 2024-Jan; Data frequency: WeeklyStep1: Use moving-window data samples to fit ARIMA(p,d,q) model to the EURUSD time series as follows:Please set your first sub-sample as the first 4-year of the data starting from 2010-Jan. Fit ARIMA to that subsample. Create the FX forecast for the subsequent 25 weeks (roughly 6 months). Calculate RMSE measure of your forecasts. Then, repeat the same process over sequential data windows moving 6-monthly steps. For example, your Sub-Sample 1 to fit the model (Training Sample) will be 2010-Week 1 to the end of 2013-Dec. (i.e. 4 years). You will generate a forecast for 2014-Jan to 2014-Jun period by using the ARIMA fitted to the Training Sample, then calculate RMSE and record it. Then, in the second step, Sub-Sample 2 Training Data will cover the 2010-Jun to 2014-Jun window, and the…
Which of the following formulas correctly calculates the acid-test ratio for 2022? Hint: Remember that Excel uses the order of operations. PARENTHESES then EXPONENTS then MULTIPLICATION and DIVISION then ADDITION and SUBTRACTION. Use parentheses around any calculations in either the numerator or denominator. Multiple Choice =+(B13+B14)/C19 =+C13+C14/C19 =+(C13+C14+C15)/C19 =+(C13+C14)/C19