AN300 EXAM 3 QUESTIONS AND ANSWERS
A record of sequential observations of an item of interest over time (e.g.,
demand/sales). - answers :a time series
Time-series forecasting is a predictive analytics technique that uses historical values of
data on an item of interest to: - answers :- uncover underlying data patterns- project the
pattern into the future- predict the outcome of the item of interest
- uncover underlying data patterns - answers :time-series forecasting
- project the pattern into the future - answers :time-series forecasting
- predict the outcome of the item of interest - answers :time-series forecasting
Data patterns of time-series forecasting - answers :• horizontal/level• trend• seasonality•
cycle
A gradual upward or downward shift in values over time. - answers :trend•
A constant average value over time. - answers :horizontal/level•
A recurring pattern that occurs at set periods within a larger time frame. - answers
:seasonality•
An alternating pattern of points lying above and below an underlying pattern (as
opposed to random fluctuation) across multiple years. - answers :cycle•
Boom and bust periods in the us economy: - answers :cycle•
Generate sales forecasts of different brands of products for production planning. -
answers :marketing application of of time-series forecasting
Predict market growth rate for strategic planning. - answers :management application of
of time-series forecasting
Generate product demand forecasts for material requirements planning. - answers
:operations application of of time-series forecasting
Sales forecasts drive production planning and operations: - answers :business
application of of time-series forecasting
Naïve forecast for the next period = - answers :actual value of the last period.
Actual value of the last period. = - answers :naïve forecast for the next period
, Require only one historical data value. - answers :naïve method
- adapt more readily to sudden shifts in the data pattern. - answers :naïve method
• for short-range (e.g. Weekly) forecasts of time-series data with a horizontal pattern. -
answers :smoothing methods
Historical moving average - answers :smoothing methods
Simple moving average - answers :smoothing methods
Exponential smoothing - answers :smoothing methods
"smooth" out the random component of the time series. - answers :smoothing methods
Slow to adapt to sudden shifts in the underlying data pattern. - answers :smoothing
methods
Historical moving average forecast for the next period = - answers :average of all prior
actual historical data.
Average of all prior actual historical data = - answers :historical moving average forecast
for the next period
The average of all prior actual data points in the time series. - answers :historical
moving average
Also known as simple average method. - answers :historical moving average
Requires no other input data except the data points in the time series. - answers
:historical moving average
Simple moving average forecast of order "k" for the next period = - answers :average of
the most recent "k" historical actual values.
Average of the most recent "k" historical actual values = - answers :simple moving
average forecast of order "k" for the next period
It requires the number of time periods used in the moving average (k) be given. -
answers :simple moving average
A time period of one results in a naïve forecast. - answers :simple moving average
Choose a small number of time periods to track movement in the most recent data
points. - answers :simple moving average
A record of sequential observations of an item of interest over time (e.g.,
demand/sales). - answers :a time series
Time-series forecasting is a predictive analytics technique that uses historical values of
data on an item of interest to: - answers :- uncover underlying data patterns- project the
pattern into the future- predict the outcome of the item of interest
- uncover underlying data patterns - answers :time-series forecasting
- project the pattern into the future - answers :time-series forecasting
- predict the outcome of the item of interest - answers :time-series forecasting
Data patterns of time-series forecasting - answers :• horizontal/level• trend• seasonality•
cycle
A gradual upward or downward shift in values over time. - answers :trend•
A constant average value over time. - answers :horizontal/level•
A recurring pattern that occurs at set periods within a larger time frame. - answers
:seasonality•
An alternating pattern of points lying above and below an underlying pattern (as
opposed to random fluctuation) across multiple years. - answers :cycle•
Boom and bust periods in the us economy: - answers :cycle•
Generate sales forecasts of different brands of products for production planning. -
answers :marketing application of of time-series forecasting
Predict market growth rate for strategic planning. - answers :management application of
of time-series forecasting
Generate product demand forecasts for material requirements planning. - answers
:operations application of of time-series forecasting
Sales forecasts drive production planning and operations: - answers :business
application of of time-series forecasting
Naïve forecast for the next period = - answers :actual value of the last period.
Actual value of the last period. = - answers :naïve forecast for the next period
, Require only one historical data value. - answers :naïve method
- adapt more readily to sudden shifts in the data pattern. - answers :naïve method
• for short-range (e.g. Weekly) forecasts of time-series data with a horizontal pattern. -
answers :smoothing methods
Historical moving average - answers :smoothing methods
Simple moving average - answers :smoothing methods
Exponential smoothing - answers :smoothing methods
"smooth" out the random component of the time series. - answers :smoothing methods
Slow to adapt to sudden shifts in the underlying data pattern. - answers :smoothing
methods
Historical moving average forecast for the next period = - answers :average of all prior
actual historical data.
Average of all prior actual historical data = - answers :historical moving average forecast
for the next period
The average of all prior actual data points in the time series. - answers :historical
moving average
Also known as simple average method. - answers :historical moving average
Requires no other input data except the data points in the time series. - answers
:historical moving average
Simple moving average forecast of order "k" for the next period = - answers :average of
the most recent "k" historical actual values.
Average of the most recent "k" historical actual values = - answers :simple moving
average forecast of order "k" for the next period
It requires the number of time periods used in the moving average (k) be given. -
answers :simple moving average
A time period of one results in a naïve forecast. - answers :simple moving average
Choose a small number of time periods to track movement in the most recent data
points. - answers :simple moving average
