QMB 3200 FINAL PAPER QUESTIONS AND
CORRECT ANSWERS FULL REVIEW GUIDE
●● Durbin-Watson test
Answer: A test to determine whether first-order autocorrelation is
present.
●● General linear model
Answer: A model of the form y=β0+β1z1+β2z2+⋯+βpzp+ε, where each
of the independent variables zj(j=1,2,...,p) is a function of x1,x2,...,xk,
the variables for which data have been collected.
●● interaction
Answer: The effect produced when the levels of one factor interact with
the levels of another factor in influencing the response variable.
The effect of two independent variables acting together.
●● variable selection procedures
Answer: Methods for selecting a subset of the independent variables for
a regression model.
,●● Time series
Answer: A sequence of observations on a variable measured at
successive points in time or over successive periods of time.
●● Mean Squared Error (MSE)
Answer: The average of the sum of squared forecast errors.
●● Time series plot
Answer: A graphical presentation of the relationship between time and
the time series variable. Time is shown on the horizontal axis and the
time series values are shown on the vertical axis.
●● horizontal pattern
Answer: A horizontal pattern exists when the data fluctuate around a
constant mean.
●● moving average
Answer: A forecasting method that uses the average of the most recent k
data values in the time series as the forecast for the next period.
●● stationary time series
Answer: A time series whose statistical properties are independent of
time. For a stationary time series the process generating the data has a
constant mean and the variability of the time series is constant over time.
, ●● trend pattern
Answer: A trend pattern exists if the time series plot shows gradual shifts
or movements to relatively higher or lower values over a longer period
of time.
●● smoothing constant
Answer: A parameter of the exponential smoothing model that provides
the weight given to the most recent time series value in the calculation of
the forecast value.
●● seasonal pattern
Answer: A seasonal pattern exists if the time series plot exhibits a
repeating pattern over successive periods. The successive periods are
often one-year intervals, which is where the name seasonal pattern
comes from.
●● cyclical pattern
Answer: A cyclical pattern exists if the time series plot shows an
alternating sequence of points below and above the trend line lasting
more than one year.
●● mean absolute error
Answer: The average of the absolute values of the forecast errors.
CORRECT ANSWERS FULL REVIEW GUIDE
●● Durbin-Watson test
Answer: A test to determine whether first-order autocorrelation is
present.
●● General linear model
Answer: A model of the form y=β0+β1z1+β2z2+⋯+βpzp+ε, where each
of the independent variables zj(j=1,2,...,p) is a function of x1,x2,...,xk,
the variables for which data have been collected.
●● interaction
Answer: The effect produced when the levels of one factor interact with
the levels of another factor in influencing the response variable.
The effect of two independent variables acting together.
●● variable selection procedures
Answer: Methods for selecting a subset of the independent variables for
a regression model.
,●● Time series
Answer: A sequence of observations on a variable measured at
successive points in time or over successive periods of time.
●● Mean Squared Error (MSE)
Answer: The average of the sum of squared forecast errors.
●● Time series plot
Answer: A graphical presentation of the relationship between time and
the time series variable. Time is shown on the horizontal axis and the
time series values are shown on the vertical axis.
●● horizontal pattern
Answer: A horizontal pattern exists when the data fluctuate around a
constant mean.
●● moving average
Answer: A forecasting method that uses the average of the most recent k
data values in the time series as the forecast for the next period.
●● stationary time series
Answer: A time series whose statistical properties are independent of
time. For a stationary time series the process generating the data has a
constant mean and the variability of the time series is constant over time.
, ●● trend pattern
Answer: A trend pattern exists if the time series plot shows gradual shifts
or movements to relatively higher or lower values over a longer period
of time.
●● smoothing constant
Answer: A parameter of the exponential smoothing model that provides
the weight given to the most recent time series value in the calculation of
the forecast value.
●● seasonal pattern
Answer: A seasonal pattern exists if the time series plot exhibits a
repeating pattern over successive periods. The successive periods are
often one-year intervals, which is where the name seasonal pattern
comes from.
●● cyclical pattern
Answer: A cyclical pattern exists if the time series plot shows an
alternating sequence of points below and above the trend line lasting
more than one year.
●● mean absolute error
Answer: The average of the absolute values of the forecast errors.
