Calculate the MAPE for each of the 3 forecast models used in the table.Which should be used for forecasting efforts, and why? A1 Month2 Jan3 Feb4Mar5Apr6 May7 Jun8 Jul9 Aug10 Sept11 Oct12 Nov13 Dec14 JanBCDEFSales ('000 Units) 5-month Moving Average Weighted moving average Exponential smoothing forecast Alpha16000 1-Alpha16,00019,0001600018,0001660015,0001688020,0001650418,00017203.222,00017362.5620,00018290.04819,00018632.038422,00018705.6307224,00019364.5045823,00020291.603661760018000186001900019800202002140018100163001830018300206002040019600209002290023200G0.20.8

Time series are used to forecast or predict the variable over the time. There are four types of…

Answered: Calculate the MAPE for each of the 3…

Calculate the MAPE for each of the 3 forecast models used in the table. Which should be used for forecasting efforts, and why?

College Algebra

1st Edition

ISBN:9781938168383

Author:Jay Abramson

Publisher:Jay Abramson

Chapter6: Exponential And Logarithmic Functions

Section6.8: Fitting Exponential Models To Data

Problem 5SE: What does the y -intercept on the graph of a logistic equation correspond to for a population...

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Calculate the forecasted values of tempurature based on weeks using Exponential Smoothing. The predicted values are calculated for you in Column C. Required: Complete the rest of the table: Week Tempurature Predicted |e| e^2 1 10 - - - 2 14 10 3 8 11.6 4 25 10.16 5 16 16.096 6 22 16.0576 7 14 18.43456 8 35 16.66074 9 15 23.99644 10 27 20.39786 11 18 23.03872 12 40 21.02323 13 28 28.61394 14 40 28.36836 15 25 33.02102 16 65 29.81261 Calculate the MAE: Calculate the MSE: In which week was forecasted tempurature the closest to the actual tempurature?
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You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”) Questions: (1) How many dummy variables do you need to create to analyze the effect of BOROUGH and MSS? Select “Manhattan” and "Non-Smoker" as a reference category. Write out all the dummy variables. (2) Write down the population model that estimates BW based on variables AGE, MSS and BOROUGH. Make sure that it is clear what each predictor means. (3) How many parallel lines are computed by model from 1i)?
(USE ONLY EXCEL SHEET FOR DATA, FORMULAS, and the GRAPHS) For the following list of data (number of sold cars in every year), apply "exponential smoothing with trend" for all the years below. (i. e find the Forecast case1 use \alpha = 0.01 and \ including trend): beta = 0.3 - - - --- case2 use: for \alpha = 0.1 and \ beta = 0.05 Calculate MAD for both cases (5 %). . Decide which case values are better and why? (5 %) Assume trend is zero for the 2012 years. Year Number of sold cars 2012 107 2013 113 2014 150 2015 133 2016 151 2017 1 Based on least squared regression method find the projections for the years 2021, 2022, and 2023. Plot the number of sold cars versus years (points graph) and show the trend line based on your projections. (5%).
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that assumes the effect of mother’s AGE at birth on infant weight BW is DIFFERENT for different levels of maternal smoking status (MSS) when adjusted for BOROUGH variable. Specify the name of each predictor in the model and/or what it means. Make sure that it is clear what each predictor means.
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1.Write down the population model that estimates BW based on variables AGE and BOROUGH(with the dummy variables). Make sure that it is clear what each predictor means. 2.How many parallel lines are computed by model from population model you created above? 3.Write down the population model that estimates BW based on variables AGE, MSS(with their dummy variables) and BOROUGH(with their dummy variables). Also write down the number of parrallel lines.…
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). Questions: 1) How many dummy variables do you need to create to analyze the effect of MSS? Select “Non-smokers” as a reference category. Write out all the dummy variables. 2)Write down the population model that estimates BW based on variables AGE and MSS. Make sure that it is clear what each predictor means. 3)How many parallel lines are computed by model from population model?
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that will properly test the effect of 3-way interaction between AGE, MSS, and BOROUGH on BW.
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time. The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “State Island”). Write down the population model that will properly test the effect of 3-way interaction between AGE, MSS, and BOROUGH on BW. THIS IS A 3 WAY INTERACTION BETWEEN THIS THREE PREDICTORS. Attached is an example.
You were asked to help with analysis of birth weights (BW) of 10,000 infants born in NYC during a certain period of time.The aim of the analysis is to see whether the birth weights of the infants are associated with mothers AGE at birth (continuous variable in years) and mothers smoking status (the maternal smoking status MSS contains 4 categories “Non-smoker”, “Past-smoker”, “Passive-smoker”, “Smoker”) and NYC boroughs (the BOROUGH variable contains 5 categories “Manhattan”, “Bronx”, “Brooklyn”, “Queens” and “Staten Island”). How many dummy variables do you need to create to analyze the effect of MSS? Select “Non-smokers” as a reference category. Write out all the dummy variables.
An economist at Nedbank ran a study of the relationship between FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017, the data collected is shown in the Table 1 below. FTSE/JSE All Shares index return (JALSH) and consumer price index (CPI) from 2006 to 2017. Year JALSH (Y) CPI (X) 2006 0.41 4.7 2007 0.19 7.1 2008 -0.23 11.5 2009 0.32 7.1 2010 0.19 4.3 2011 0.03 5.0 2012 0.27 5.6 2013 0.21 5.7 2014 0.11 6.1 2015 0.05 4.6 2016 0.00 6.4 2017 0.21 5.3 The estimated regression…