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Professor Very Busy needs to allocate time next week for office hours. To do this, he needs to forecast the number of students who will seek appointments. He has gathered the following data:

| Week | #Students |
|--------------------|-----------|
| 6 Weeks ago | 83 |
| 5 Weeks ago | 110 |
| 4 Weeks ago | 95 |
| 3 Weeks ago | 80 |
| 2 Weeks ago | 65 |
| Last week | 50 |

What is this week's forecast using exponential smoothing with \(\alpha = 0.2\), if the forecast for two weeks ago was 90?

A. 49
B. 77
C. 52
D. 50
E. 65

Answer :

Answer:

b. 77

Explanation:

The formula for forecasting is :

[tex]F_{t}[/tex] = [tex]\alpha D_{t-1}[/tex] + (1 - [tex]\alpha[/tex]) [tex]F_{t-1}[/tex]

where [tex]F_{t}[/tex] is forecast for the period and [tex]D_{t}[/tex] is the actual demand for the period.

Last week forecast is = [tex]\alpha[/tex] * Demand 2 weeks ago + (1 - [tex]\alpha[/tex]) * Forecast 2 weeks ago

0.2 * 65 + (1 - .02) * 90 = 13

Current week forecast is = [tex]\alpha[/tex] * Demand Last weeks + (1 - [tex]\alpha[/tex]) * Forecast Last weeks

0.2 * 50 + (1 - 0.2) * 83 = 77.

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Rewritten by : Barada

Final answer:

Using exponential smoothing with alpha = 0.2, the forecast for this week's number of students seeking appointments is 52.

Explanation:

To forecast this week's number of students seeking appointments, Professor Very Busy can use exponential smoothing. Exponential smoothing is a time series forecasting method that assigns exponentially decreasing weights to older observations. The forecast for this week is calculated by multiplying the forecast for the previous week by 0.2 and adding it to 0.8 times the actual number of students from last week. Using alpha = 0.2 and the given data, the forecast for this week is:



Forecast for this week = alpha × (last week's actual number of students) + (1-alpha) × (previous week's forecast)



Forecast for this week = 0.2 × 50 + 0.8 × 90 = 52

Learn more about Exponential smoothing here:

https://brainly.com/question/31358866

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