Question

Use a smoothing constant of α = 0.4 to compute the exponential smoothing forecasts. Time Series Value Week Forecast Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using α = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.2. The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.4. The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.4. The exponential smoothing using α = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.2.

          Use a smoothing constant of α = 0.4 to compute the exponential smoothing forecasts.
Time Series Value
Week
Forecast
Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain.
The exponential smoothing using α = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.2.
The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.4.
The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.4.
The exponential smoothing using α = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.2.

Show more…

use smoothing constant of a 04 to compute the exponential smoothing forecasts time series value week forecast does smoothing constant of 02 or 04 appear to provide more accurate forecasts ba 90592

Added by Rosa P.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

Instant Answer

Solved by Expert Maitreya E

06/28/2022

Step 1

4 for each week from 1 to 6. Given: - Week 1: 8 - Smoothing constant (alpha) = 0.4 Using the formula: \[ s_t = \alpha \times x_{t-1} + (1 - \alpha) \times s_{t-1} \] Calculate the forecasts for each week: - Week 2: \( s_2 = 0.4 \times 8 + 0.6 \times 8 = 15.2 Show more…

Show all steps

lock

Thanks for your feedback!

Use a smoothing constant of α = 0.4 to compute the exponential smoothing forecasts. Time Series Value Week Forecast Does a smoothing constant of 0.2 or 0.4 appear to provide more accurate forecasts based on MSE? Explain. The exponential smoothing using α = 0.4 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.2. The exponential smoothing using α = 0.2 provides a better forecast since it has a smaller MSE than the exponential smoothing using α = 0.4. The exponential smoothing using α = 0.2 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.4. The exponential smoothing using α = 0.4 provides a better forecast since it has a larger MSE than the exponential smoothing using α = 0.2.

Play audio

Feedback

Powered by NumerAI

Maitreya E and 56 other subject Intro Stats / AP Statistics educators are ready to help you.

Ask a new question

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Key Concepts

Recommended Videos

Recommended Textbooks

Transcript

00:01 Hello everyone.

00:03 We are asked to use the smoothing constant alpha is equal to 0 .4 to compute the exponential smoothing forecast and we are given the following table.

00:12 We are given the week time series value and we need to forecast for the time series value, which appears more accurate.

00:19 0 .2 or 0 .4 based on the mse.

00:24 So now let's start to solve the problem.

00:28 First of all from the given data we are given the time in weeks that is going to go from 1 to 6 right let t is equal to 1 then s 1 is equal to x not which is equal to 8 in the first rally now when t is equal to 2 the formula would be s t is equal to alpha x t minus 1 plus 1 minus alpha s t minus 1 so now let's substitute the values.

01:01 So we are going to get s2 is equal to alpha x2 minus 1 is going to be 1 plus 1 minus alpha.

01:12 S2 minus 1 is going to be s1.

01:14 Now let's substitute the value.

01:16 S2 is going to be 0 .4x1 plus 0 .6 s1.

01:27 So s2 is going to be 4 .4 plus 10 .8 or s2 is going to be 15 .2.

01:38 Similarly, we need to proceed and solve for all the values.

01:42 So now let's start doing it.

01:45 Now, for t is equal to 3.

01:48 So t is equal to 3 implies s3 is equal to 0 .4 x2 plus 0 .6 s2.

02:04 Subcute the radius now.

02:05 We are going to get this to be equal to 5 .2 plus 9 .12.

02:11 So s3 is going to be 14 .32.

02:17 Now let's proceed for the value.

02:20 T is equal to 4.

02:24 So what happens when t is equal to 4? we have s3.

02:30 We have found s3.

02:31 So using s3 i'm going to find s4.

02:33 Will be equal to 0 .4 x3 plus 0 .6 s3...

Ace is your personal tutor. It breaks down any question with clear steps so you can learn.

Start Using Ace

Continue solving this problem

Create a free account to:

View full step-by-step solution
Ask follow-up questions with Ace AI
Save progress and study later