MODULE 9 QMB3200 UCF QUESTIONS AND ANSWERS 2024

The difference between the actual time series value and the forecast is called: forecast error. In the linear trend equation, Tt = b0 + b1t, b0 represents the: y- intercept of the trend line. The time series model that is appropriate in situations where the seasonal fluctuations do not depend upon the level of the time series is: an additive model. A time series from which the effect of season has been removed by dividing each original time series observation by the corresponding seasonal index is called a: deseasonalized time series. Which of the following is not present in a time series? Operational variations If data for a time series analysis is collected on an annual basis only, which component may be ignored? Seasonal Time series regression refers to the use of regression analysis when the independent variable is: time. When using a weighted moving average, if we believe that the recent past is a better predictor of the future than the distant past, we should: give larger weights to recent observations. Three of the following forecasting methods are appropriate for a time series with a horizontal pattern. Which one is not appropriate for a time series with a horizontal pattern? Linear trend regression When using a categorical variable in a multiple regression model that has k levels, how many dummy variables are needed? k - 1 A forecast model of the form Tt=b0+b1t+b2t^2 is called a(n): quadratic trend equation. The time series component that reflects gradual variability over a long time period is called: a trend. The following linear trend expression was estimated using a time series with 9 years as the independent variable and annual profit as the response variable (in millions). Tt = 29.2 + 3.8t The value 3.8 represents the: amount that the profit is expected to increase by each year, in millions of dollars, on average. The average of the sum of squared forecast errors is called: mean squared error. Which of the following exponential smoothing constant values puts the same weight on the most recent time series value as does a 5-period moving average? a = .2 If the historical data are restricted to past values of the variable to be forecast, the forecasting procedure is called a: time series method. The average of the absolute values of the forecast errors is called: mean absolute error. When historical data on the variable being forecast are either not applicable or unavailable, what kind of forecasting method should be used? Qualitative methods All of the following are true about qualitative forecasting methods except: they assume that the pattern of the past will continue into the future. What is the component of a time series model that is attributable to multiyear cycles in the time series? The cyclical component The average of all the historical data will always provide the best results as long as the underlying time series is: stationary. What kind of forecasting method is based on the assumption that the variable we are forecasting has a cause-effect relationship with one or more other variables? Casual forecasting method