UCF QMB 3200 LATEST 2026 EVALUATION
TEST QUESTIONS AND ANSWERS SURE A+
✔✔Estimated regression equation - ✔✔The estimate of the regression equation
developed from sample data by using the least squares method. For simple linear
regression, the estimated regression equation is ŷ = b0 + b1x.
✔✔Scatter diagram - ✔✔A graph of bivariate data in which the independent variable is
on the horizontal axis and the dependent variable is on the vertical axis.
✔✔Coefficient of determination - ✔✔A measure of the goodness of fit of the estimated
regression equation. It can be interpreted as the proportion of the variability in the
dependent variable y that is explained by the estimated regression equation.
✔✔Standard error of the estimate - ✔✔The square root of the mean square error,
denoted by s. It is the estimate of σ, the standard deviation of the error term ϵ.
✔✔Confidence interval - ✔✔The interval estimate of the mean value of y for a given
value of x.
✔✔Prediction interval - ✔✔The interval estimate of an individual value of y for a given
value of x.
, ✔✔Residual plot - ✔✔Graphical representation of the residuals that can be used to
determine whether the assumptions made about the regression model appear to be
valid.
✔✔Time series - ✔✔A sequence of observations on a variable measured at successive
points in time or over successive periods of time.
✔✔Mean squared error (MSE) - ✔✔The average of the sum of squared forecast errors.
✔✔Time series plot - ✔✔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 - ✔✔A horizontal pattern exists when the data fluctuate around a
constant mean.
✔✔Moving averages - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 (MAE) - ✔✔The average of the absolute values of the forecast
errors.
✔✔ Parameter - ✔✔A numerical characteristic of a population, such as a population
mean µ, a population standard deviation σ, a population proportion p, and so on.
TEST QUESTIONS AND ANSWERS SURE A+
✔✔Estimated regression equation - ✔✔The estimate of the regression equation
developed from sample data by using the least squares method. For simple linear
regression, the estimated regression equation is ŷ = b0 + b1x.
✔✔Scatter diagram - ✔✔A graph of bivariate data in which the independent variable is
on the horizontal axis and the dependent variable is on the vertical axis.
✔✔Coefficient of determination - ✔✔A measure of the goodness of fit of the estimated
regression equation. It can be interpreted as the proportion of the variability in the
dependent variable y that is explained by the estimated regression equation.
✔✔Standard error of the estimate - ✔✔The square root of the mean square error,
denoted by s. It is the estimate of σ, the standard deviation of the error term ϵ.
✔✔Confidence interval - ✔✔The interval estimate of the mean value of y for a given
value of x.
✔✔Prediction interval - ✔✔The interval estimate of an individual value of y for a given
value of x.
, ✔✔Residual plot - ✔✔Graphical representation of the residuals that can be used to
determine whether the assumptions made about the regression model appear to be
valid.
✔✔Time series - ✔✔A sequence of observations on a variable measured at successive
points in time or over successive periods of time.
✔✔Mean squared error (MSE) - ✔✔The average of the sum of squared forecast errors.
✔✔Time series plot - ✔✔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 - ✔✔A horizontal pattern exists when the data fluctuate around a
constant mean.
✔✔Moving averages - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 - ✔✔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 (MAE) - ✔✔The average of the absolute values of the forecast
errors.
✔✔ Parameter - ✔✔A numerical characteristic of a population, such as a population
mean µ, a population standard deviation σ, a population proportion p, and so on.
