QMB3200 UCF MOD 7-9 VOCAB QUESTIONS AND ANSWERS 2024

General Linear Model 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 the effect of two independent variable acting together variable selection procedures Methods for selecting a subset of the independent variables for a regression model. Autocorrelation correlation in the errors that arises when the error term at successive points in time are related Serial Correlation the same as autocorrelation Durbin-Watson test A test to determine whether first-order Autocorrelation is present multiple regression analysis regression analysis involving two or more independent variables multiple regression model The mathematical equation that describes how the dependent variable y is related to the independent variables x1,x2,...,xp and an error term E. multiple regression equation the mathematical equation relating the expected value or mean value of the dependent variable to the values of the independent variables estimated multiple regression equation the estimate of the multiple regression equation based on sample data and the least squares method least squares method The method used to develop the estimated regression equation. It minimizes the sum of squared residuals (the deviations between the observed values of the dependent variable, yi, and the estimated values of the dependent variable, y^i). multiple coefficient of determination A measure of the goodness of fit of the estimated multiple regression equation. It can be interpreted as the proportion of the variability in the dependent variable that is explained by the estimated regression equation. adjusted multiple coefficient of determination A measure of the goodness of fit of the estimated multiple regression equation that adjusts for the number of independent variables in the model and thus avoids overestimating the impact of adding more independent variables. Multicollinearity The term used to describe the correlation among the independent variables. categorical independent variable an independent variable with categorical data dummy or indicator variable A variable used to model the effect of categorical independent variables. A dummy variable may take only the value zero or one. time series a sequence of observations on a variable measured at successive points in time or over successive periods of time 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. Stationary time series A time series whose statistical properties are independent of time. 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. seasonal pattern exists if the time series plot exhibits a repeating pattern over successive periods. The successive periods are often one-year intervals. 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. forecast error The difference between the actual time series value and the forecast. Mean Absolute Error the average of the absolute values of the forecast errors mean squared error the average of the sum of squared forecast errors mean absolute percent error the average of the absolute values of the percentage forecast errors moving average 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. Weighted Moving Average a forecast method that involves selecting a different weight for the most recent K data values in the time series and then computing a weighted average of the values. Exponential Smoothing A forecasting method that uses a weighted average of past time series values as the forecast 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.