DATA MINING EXAM GUIDE
QUESTIONS AND ANSWERS 2025/2026
1. (T/F) A short coming of a moving average is that it does not forecast seasonal
component. - Answer-True
T/F: MSE is a measure of the average of the errors absolute value. - Answer-False
T/F: Seasonality accounts for the gradual shifting of the time series over a long
period of time. - Answer-false
T/F- To determine the seasonal factor of a time-series data set, it is important to
develop an average for the same quarters in each period and then find a seasonal
factor by dividing that average by the general average. - Answer-True
T/F: the four components of time series is level, trend, seasonality, and noise. -
Answer-True
The fifth step of decomposition is:
a) Deseasonalize the original data
b) Determine the seasonal factor
c) Create the final forecast by adjusting the regression line by the seasonal factor
d) Project the regression line through the period of the forecast - Answer-Create the
final forecast by adjusting the regression line by the seasonal factor
1) What type of polynomial trend line is this? Y= a+b1X+b2X2+ b3X3
A) Linear
B) Quadratic
C) Cubic - Answer-Quadratic
T/F: There are three different types of forecasting - Answer-True
The first step of decomposition is:
a. determine the seasonal factor
b. create forecast by adjusting regression
c. determine the trend factor
d. deseasonalize the date - Answer-determine the seasonal factor
T/F- A weighted moving average allows unequal weighting of prior time periods. -
Answer-True
Which time series component describes the average value of the series?
a. Level
b. Trend
c. Seasonality
d. Noise - Answer-Level
T/F Positive lag-1 reflects swings in the series. - Answer-False
, True or False: Random partitioning will leave holes in the data. - Answer-True
Which piece of data is NOT needed for simple exponential smoothing?
A. The actual demand that occurred for that forecast period.
B. A smoothing constant Alpha
C. The most recent forecast
D. A smoothing constant Beta. - Answer-A smoothing constant alpha
1.) True or False: Smoothing methods rely on local data, not mathematical structure
- Answer-True
Which of the following accounts for regular patterns over a year?
a.) Noise
b.) Level
c.) Trend
d.) Seasonality - Answer-Seasonality
For the components of time-series, accounts for the gradual shifting of the time
series over a long period of time and accounts for regular patterns over a year.
trend; seasonality
noise; seasonality
trend; level
level; seasonality - Answer-A: Trend; Seasonality
T/F The mean squared error (MSE) is an often-used measure of the accuracy of a
forecasting method - Answer-True
T/f -Data mining - is the enterprise resource planning approach to supply chain
management - Answer-False
Multiple Choice: Which partition is used to to assess the performance of the chosen
model with new data?
A) Training
B) New
C) Validation
D) Test - Answer-D) Test
T/F: Data science refers to business analytics methods that go beyond counts,
descriptive techniques, reporting, and methods based on business rules. - Answer-
False
QUESTIONS AND ANSWERS 2025/2026
1. (T/F) A short coming of a moving average is that it does not forecast seasonal
component. - Answer-True
T/F: MSE is a measure of the average of the errors absolute value. - Answer-False
T/F: Seasonality accounts for the gradual shifting of the time series over a long
period of time. - Answer-false
T/F- To determine the seasonal factor of a time-series data set, it is important to
develop an average for the same quarters in each period and then find a seasonal
factor by dividing that average by the general average. - Answer-True
T/F: the four components of time series is level, trend, seasonality, and noise. -
Answer-True
The fifth step of decomposition is:
a) Deseasonalize the original data
b) Determine the seasonal factor
c) Create the final forecast by adjusting the regression line by the seasonal factor
d) Project the regression line through the period of the forecast - Answer-Create the
final forecast by adjusting the regression line by the seasonal factor
1) What type of polynomial trend line is this? Y= a+b1X+b2X2+ b3X3
A) Linear
B) Quadratic
C) Cubic - Answer-Quadratic
T/F: There are three different types of forecasting - Answer-True
The first step of decomposition is:
a. determine the seasonal factor
b. create forecast by adjusting regression
c. determine the trend factor
d. deseasonalize the date - Answer-determine the seasonal factor
T/F- A weighted moving average allows unequal weighting of prior time periods. -
Answer-True
Which time series component describes the average value of the series?
a. Level
b. Trend
c. Seasonality
d. Noise - Answer-Level
T/F Positive lag-1 reflects swings in the series. - Answer-False
, True or False: Random partitioning will leave holes in the data. - Answer-True
Which piece of data is NOT needed for simple exponential smoothing?
A. The actual demand that occurred for that forecast period.
B. A smoothing constant Alpha
C. The most recent forecast
D. A smoothing constant Beta. - Answer-A smoothing constant alpha
1.) True or False: Smoothing methods rely on local data, not mathematical structure
- Answer-True
Which of the following accounts for regular patterns over a year?
a.) Noise
b.) Level
c.) Trend
d.) Seasonality - Answer-Seasonality
For the components of time-series, accounts for the gradual shifting of the time
series over a long period of time and accounts for regular patterns over a year.
trend; seasonality
noise; seasonality
trend; level
level; seasonality - Answer-A: Trend; Seasonality
T/F The mean squared error (MSE) is an often-used measure of the accuracy of a
forecasting method - Answer-True
T/f -Data mining - is the enterprise resource planning approach to supply chain
management - Answer-False
Multiple Choice: Which partition is used to to assess the performance of the chosen
model with new data?
A) Training
B) New
C) Validation
D) Test - Answer-D) Test
T/F: Data science refers to business analytics methods that go beyond counts,
descriptive techniques, reporting, and methods based on business rules. - Answer-
False
