Consider the following time series data:5MonthValue136219.583094181028.511634.512722.513For the naïve forecasting method and the MA2 forecasting method complete the following table:1415Forecasting MethodMAEMSEМАРЕ16Naïve17MA21819Based on the relative forecast error reported here which of the two forecasted methods would you choose.20212223242526

Suppose we have a certain number of years, and a certain number of values associated with the…

Consider the following time series data: Month Value 1 36 2 19.5 3 30 4. 18 5 28.5 34.5 22.5 For the naïve forecasting method and the MA2 forecasting method complete the following table: Forecasting Method МАЕ MSE МАРЕ Naïve MA2 Based on the relative forecast error reported here which of the two forecasted methods would you choose. 67

Consider the following time series data: Month Value 1 36 2 19.5 3 30 4. 18 5 28.5 34.5 22.5 For the naïve forecasting method and the MA2 forecasting method complete the following table: Forecasting Method МАЕ MSE МАРЕ Naïve MA2 Based on the relative forecast error reported here which of the two forecasted methods would you choose. 67

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.5: Comparing Sets Of Data

Problem 13PPS

See similar textbooks

Similar questions

What is the best predicted value of y?
Examining the below R output, explain what model was selected for forecasting?
Is there a less complex way to solve this problem? S13. Consider the data showing the number of bikes sold by a specialized market over the past 10 weeks. Week: 1 2 3 4 5 6 7 8 9 10Sales: 15 20 17 18 16 22 25 18 20 19(a). Compute forecasts using a 3-week moving average. (MSE-?).(b). Use weighted moving average selecting weights for the data values. (MSE-?).(c). Apply exponential smoothing with the smoothing constant . (MSE-?).
Explain whether each scenario below is a regression, classification, or unsupervised learn- ing problem. If it is a supervised learning scenario, indicate whether we are more interested in inference or prediction. Finally, provide in each case the number of observations, n, and the number of predictors, p. (1) An online retailer must decide whether to display advertisement A or advertisement B to each customer on the basis of collected customer demographics (age, income, zip code, and gender). A set of 150 of its customers have already expressed a preference for one advertisement or the other. (2) A policy analyst is interested in discovering factors that are associated with the crime rate across different U.S. cities. For each of 500 cities, the policy analyst gathers the following data: the crime rate, unemployment rate, population, median income, median home price, and state. (3) The the channel owner to see where the subscribers are located, their age and gender, the times and days…
use given data and perform forecasting using 4-week moving average, weighted moving average (7/10; 1/5; 1/10)...define which of those 3 methods gives more precise forecasts... 2 decimal places for all calculations