AN 300 FiNAl ExAm QUESTioNS AND corrEcT ANSWErS (vEriFiED) |
lATEST UPDATE 2026/2027 | grADED A+ | BrAND NEW | 100%
gUArANTEED PASS
Which of the following statements about time-series forecasting is TRUE? - ANSWER-It is a
predictive analytics technique.
It applies to strategic planning by predicting market growth rate.
It predicts the future outcome of the item of interest.
It needs data on observations of an item of interest over time.
Types of data patterns - ANSWER-Horizontal- constant avg. value over time
Trend- a gradual upward or downward shift in values over time
Seasonality- a recurring pattern that occurs at set periods within a larger time frame
Cycle- an alternating pattern of points lying above and below an underlying pattern (as opposed
to random fluctuation) across multiple years (ex. boom and bust periods in US economy)
Seasonality - ANSWER-A recurring pattern that occurs at set periods within a larger time frame.
Upward trend - ANSWER-A gradual increase in values over time
downward trend - ANSWER-A gradual decrease in values over time
Level - ANSWER-A constant average value over time
Which of the following is a business application of time series forecasting? - ANSWER-Sales
forecasts of swimsuits from past records
Given the following sales data (in $000) for C&A's product:
January 15
February 18
, March 14
April 16
May 13
June 16
What is the naive forecast for June?
What is the historical moving average forecast for July?
What is the simple moving average forecast of order 3 for June?
What is the simple moving average forecast of order 1 for June?
What is the exponential smoothing forecast for July if alpha = 0.2 and the forecast for February is
15?
The simple moving average method of order 1 is the same as the Naive method. - ANSWER-13
15.33
14.33
13
15.15
T
Naive - ANSWER-It requires only one historical data value.
It adapts readily to sudden shifts in data pattern.
Simple moving average - ANSWER-It requires the data points in the time series as well as the
number of periods used in forecasting.
Exponential smoothing average - ANSWER-It is a weighted average of all prior historical actual
vales.
Linear regression - ANSWER-It uses the "best fit" linear trend line to make predictions.
Linear regression for seasonality - ANSWER-It uses indicator variables to capture variations.
Which of the following statements about time-series forecasting methods is TRUE? - ANSWER-
Linear Regression for Seasonality without Trend method is appropriate for data with a seasonal
pattern only.
lATEST UPDATE 2026/2027 | grADED A+ | BrAND NEW | 100%
gUArANTEED PASS
Which of the following statements about time-series forecasting is TRUE? - ANSWER-It is a
predictive analytics technique.
It applies to strategic planning by predicting market growth rate.
It predicts the future outcome of the item of interest.
It needs data on observations of an item of interest over time.
Types of data patterns - ANSWER-Horizontal- constant avg. value over time
Trend- a gradual upward or downward shift in values over time
Seasonality- a recurring pattern that occurs at set periods within a larger time frame
Cycle- an alternating pattern of points lying above and below an underlying pattern (as opposed
to random fluctuation) across multiple years (ex. boom and bust periods in US economy)
Seasonality - ANSWER-A recurring pattern that occurs at set periods within a larger time frame.
Upward trend - ANSWER-A gradual increase in values over time
downward trend - ANSWER-A gradual decrease in values over time
Level - ANSWER-A constant average value over time
Which of the following is a business application of time series forecasting? - ANSWER-Sales
forecasts of swimsuits from past records
Given the following sales data (in $000) for C&A's product:
January 15
February 18
, March 14
April 16
May 13
June 16
What is the naive forecast for June?
What is the historical moving average forecast for July?
What is the simple moving average forecast of order 3 for June?
What is the simple moving average forecast of order 1 for June?
What is the exponential smoothing forecast for July if alpha = 0.2 and the forecast for February is
15?
The simple moving average method of order 1 is the same as the Naive method. - ANSWER-13
15.33
14.33
13
15.15
T
Naive - ANSWER-It requires only one historical data value.
It adapts readily to sudden shifts in data pattern.
Simple moving average - ANSWER-It requires the data points in the time series as well as the
number of periods used in forecasting.
Exponential smoothing average - ANSWER-It is a weighted average of all prior historical actual
vales.
Linear regression - ANSWER-It uses the "best fit" linear trend line to make predictions.
Linear regression for seasonality - ANSWER-It uses indicator variables to capture variations.
Which of the following statements about time-series forecasting methods is TRUE? - ANSWER-
Linear Regression for Seasonality without Trend method is appropriate for data with a seasonal
pattern only.
