Are regularly repeating upward or downward movements in series values that can be tied to recurring events?
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A statement about the future value of a variable of interest. Show The first basic step in the forecasting process Determine the Purpose of the Forecast The second basic step in the forecasting process. The third basic step in the forecasting process. Obtain, clean, and analyze appropriate data The fourth basic step in the forecasting process Select a forecasting technique The fifth basic step in the forecasting process The sixth basic step in the forecasting process Monitor the forecast errors Difference between the actual value and the value that was predicted for a given period. The average absolute forecast error. The average of squared forecast errors. The average absolute percentage error. Mean Absolute Percent Error Approach to forecasting that consists mainly of subjective inputs. Approach to forecasting that involves either the projection of historical data or the development of associative models that attempt to use causal variables to make a forecast. Type of information which includes human factors, personal opinions, and hunches. Type of data that is objective information. Forecasts that use subjective inputs such as opinions to form consumer surveys, sales staff, managers, executives, and experts. Forecasts that project patterns identified in recent time-series observations. Forecasting technique that uses explanatory variables to predict future demand. An iterative process in which managers and staff complete a series of questionnaires, each developed from the previous one, to achieve a consensus forecast. A time-ordered sequence of observations taken at regular intervals. A long-term upward or downward movement in data. Short-term regular variations related to the calendar or time of day. Wavelike variations lasting more than one year. Caused by unusual circumstances, not reflective of typical behavior. A forecast for any period that equals the previous period's actual value. Technique that averages a number of recent actual values, updated as new values become available. More recent values in a series are given more weight in computing a forecast. A weighted averaging method based on previous forecast plus a percentage of the forecast error. Using the forecasting method that demonstrates the best recent success. Used to develop forecasts when trend is present. Variation of exponential smoothing used when a time series exhibits a linear trend. Trend-Adjusted Exponential Smoothing
Regularly repeating movements in series values that can be tied to recurring events. The seasonal percentage applied in the multiplicative model. Variables that can be used to predict values of the variable of interest. Technique for fitting a line to a set of points. Minimizes the sum of the squared vertical deviations around the line. A measure of the scatter of points around a regression line. Standard Error of Estimate A measure of the strength and direction of relationship between two variables. A visual tool for monitoring forecast errors. The ratio of cumulative forecast error to the corresponding value of MAD, used to monitor a forecast. Persistent tendency for forecasts to be greater or less than the actual values of a time series. Type of error that occurs when the forecast is too low. Type of error that is the difference between the actual and predicted values in a given period. Type of error that occurs when the forecast is too high. Alternate name for seasonal relative. The essence of associative techniques is the development of an equation that summarizes the effects of _____ In time-series data, _____ are regularly repeating upward or downward movements in series values that can be tied to recurring events. _____ forecasts pertain to ongoing operations. _____ forecasts are an important strategic planning tool. Represents an error of zero on a control chart. Exponential Smoothing Forecast Ft = Ft-1 + a(At-1 - Ft-1) Formula for error in period t A value of 0.25 or less of r^2 indicates a _____ predictor. A value between 0.25 and 0.8 of r^2 indicates a _____ predictor. Formula for trend-adjusted exponential smoothing forecast. Represents the absolute forecast error. Measures the percentage of variation in the values of the dependent variable that is "explained" by the independent variable. Model in which predictions are made on demand for an established product. Often used to develop long-range plans and new product development. A tracking signal compares the cumulative forecast error to the MAD in order to detect any _____ over time. In the equations for the coefficients of a line, what is the a term? In the equations for the coefficient of a line, what is the b term? In the equations for the coefficients of a line, what is the y term? Is a time series model which usually have a gradual upward and downward movement of data overtime?Trend (T) is the gradual upward or downward movement of the data over time. Seasonality (S) is a pattern of demand fluctuations above or below trend line that repeats at regular intervals.
Is an up and down movement in demand that repeats itself over a period of more than a year?Answer and Explanation: A cyclical pattern is an up-or-down repetitive movement that repeats itself over a time span of more than 1 year.
What are the 4 forecasting methods?While there are a wide range of frequently used quantitative budget forecasting tools, in this article we focus on the top four methods: (1) straight-line, (2) moving average, (3) simple linear regression, and (4) multiple linear regression.
Which demand trend type is one that repeats itself over time?Seasonal pattern: Oscillating movement in demand that occurs periodically in the short run.
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