MGO 302 Lecture Notes - Lecture 2: Seasonality, Time Series, Exponential Smoothing
20 Jun 2018
School
Department
Course
Professor
EQS Module 2
Question 1
1.
In a recent survey, a 21-year old gave a movie a score of 2, while a 52-year old gave it a
score of 3, a 36-year old gave it a score of 10 and a 32-year old gave it a score of
2. Based on these four surveys, what is the correlation between age of movie-goer and
score for the movie?
-0.72
0.96
0.15
-0.98
0.51 x
Question 3
1.
A forecast which is calculated by taking the previous forecast and adding some
percentage of the previous forecast's error is:
a linear regression forecast x
an exponential smoothing forecast
a deseasonalized forecast
a moving averages forecast
a weighted moving averages forecast
1 points
Question 4
1.
You are observing the sales department staff, who use exponential smoothing to forecast
monthly sales. Their forecast for September's sales was 10,000 units. September's actual
sales figure became available yesterday: 8,000 units were sold in September. Today, the
sales department announced their sales forecast of 9,300 units for October. What "alpha"
(smoothing constant) are they using to forecast sales?
0.35
0.9
0.65
0.05
0.5
1 points
Question 5
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1.
Which of the following is (are) true statements?
I. Time series techniques involve identification of explanatory variables that can be used
to predict future demand.
II. A moving average forecast tends to be more responsive to changes in the data series
when more data points are included in the average, also known as increasing the “span”
of the average.
III. In exponential smoothing, an alpha of 0.30 will cause a forecast to react more quickly
to a large error than will an alpha of 0.20.
I and II x
III only
I only
I, II and III
II only
1 points
Question 6
1.
Why would the issue of customer perception of quality cause more difficulties for service
companies than manufacturing companies?
Because services are usually less labor intensive.
Because service companies usually require more investment in equipment.
Because the service product itself is intangible.
Because service companies can’t keep their product in inventory.
Because more customers buy services than manufactured goods.
Question 1
1.
Given an actual demand of 105, a predicted value of 97, and an "alpha" of 0.4, the simple
exponential smoothing forecast for the next period would be:
80.8
93.8
100.2
101.8
108.2
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1 points
Question 2
1.
In a recent survey, a 24-year old gave a movie a score of 9, while a 72-year old gave it a
score of 3, a 35-year old gave it a score of 8 and a 41-year old gave it a score of 6. Based
on these four surveys, what is the correlation between age of movie-goer and score for
the movie?
-0.72
0.51 x
0.15 x
0.96 x
-0.98 x
1 points
Question 3
1.
Given forecast errors of 5, 0, -4, and 3, what is the mean absolute deviation (MAD) ?
1
3
4
1.333
2.5
1 points
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Document Summary
You are observing the sales department staff, who use exponential smoothing to forecast monthly sales. Their forecast for september"s sales was 10,000 units. September"s actual sales figure became available yesterday: 8,000 units were sold in september. Today, the sales department announced their sales forecast of 9,300 units for october. Which of the following is (are) true statements: time series techniques involve identification of explanatory variables that can be used to predict future demand. A moving average forecast tends to be more responsive to changes in the data series when more data points are included in the average, also known as increasing the span of the average. In exponential smoothing, an alpha of 0. 30 will cause a forecast to react more quickly to a large error than will an alpha of 0. 20. Because service companies usually require more investment in equipment. Because service companies can"t keep their product in inventory. Because more customers buy services than manufactured goods.
