AN 300 Final Exam Question and
answers already pass 2025/2026
Which of the following statements about time-series forecasting is TRUE? - correct 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 - correct 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 - correct answer ✔A recurring pattern that occurs at set periods within a larger time frame.
Upward trend - correct answer ✔A gradual increase in values over time
downward trend - correct answer ✔A gradual decrease in values over time
Level - correct answer ✔A constant average value over time
Which of the following is a business application of time series forecasting? - correct 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. - correct answer ✔13
15.33
14.33
13
15.15
T
Naive - correct answer ✔It requires only one historical data value.
It adapts readily to sudden shifts in data pattern.
Simple moving average - correct answer ✔It requires the data points in the time series as well as the
number of periods used in forecasting.
answers already pass 2025/2026
Which of the following statements about time-series forecasting is TRUE? - correct 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 - correct 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 - correct answer ✔A recurring pattern that occurs at set periods within a larger time frame.
Upward trend - correct answer ✔A gradual increase in values over time
downward trend - correct answer ✔A gradual decrease in values over time
Level - correct answer ✔A constant average value over time
Which of the following is a business application of time series forecasting? - correct 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. - correct answer ✔13
15.33
14.33
13
15.15
T
Naive - correct answer ✔It requires only one historical data value.
It adapts readily to sudden shifts in data pattern.
Simple moving average - correct answer ✔It requires the data points in the time series as well as the
number of periods used in forecasting.
