The forecasting method that is appropriate when the time series
has no significant trend, cyclical, or seasonal pattern is
Correct option is moving average forecast
(since for no trend the pattern is horizontal and forecasted value can be taken by averaging out of the past data)
The forecasting method that is appropriate when the time series has no significant trend, cyclical, or...
5. The components of time-series are: a. Trend, Seasonal, Movement, and Random b. Trend, Mobility, Cyclical, and Seasonal c. Trend, Seasonal, Cyclical, and Random d. Trend, Seasonal, Cyclical, and Perfection The mean absolute deviation measures the accuracy of a forecast by calculating.. a. the mid-point of absolute forecasting error per period of historical data. b. the average absolute forecasting error per period of historical data. c. the standard deviation of absolute forecasting error per period of historical data d. both...
The following statements regarding Deterministic Trend-forecasting models are correct ,EXCEPT May be adjusted for seasonal, secular and cyclical trends in the data Based on an extrapolation of past values into the future. easy to develop and maintain Can help to Identify major future changes in the direction of an economic data series
-QL18 > Discussions > (4.2) Discussion - Chapter 11 - Forecasting and Time Series - due Thursday/Sunday du This is a graded discussion: 25 points possible (4.2) Discussion - Chapter 11 - Forecasting and Time Series - due Thursday/Sunday Review the section on forecasting and time series in Chapter 11. Due Thursday: (This portion worth 15 points) • Discuss three or four forecasting issues that you encounter in your daily life. How do you make your forecasts? • Provide two...
what did you think time series pattern exciti ? Trend ,seasonal ,horizontal ?
Different types of time-series forecasting models and their applicability in different organizations are given below: 1. Naive approach: In naive approach, demand for the next period is assumed to be same in the most recent period. This method can be used in economic and financial time series analysis. It can be used to forecast demand for mature products having level or seasonal demand without a trend. 2. Moving average: This method uses a number of historical data to determine the...
1: Please select the right statement(s) that apply to the exponential smoothing with trend adjustment forecasting method Select one or more: a. The exponential smoothing with trend adjustment requires the initial forecast b. The use of exponential smoothing with trend adjustment is appropriate when the underlying average of the time series is either increasing or decreasing c. α and β should be carefully selected between 0 and 1 in a way to minimize the forecasting errors d. Setting α close...
quantitative QUESTION 15 Given is a time series. What is the time series demand pattern as below? Date Price 6/26/2012 121.34 6/27/2012 102.56 6/28/2012 98.67 6/29/2012 99.6 7/2/2012 102.32 7/3/2012 95.23 7/5/2012 89.34 7/6/2012 82.37 79.56 7/10/2012 81.23 7/11/2012 72.67 7/12/2012 69.23 7/13/2012 62.85 7/16/2012 57.87 7/17/2012 58.23 7/9/2012 Horizontal Trend-Downward O Seasonal Trend and Seasonal Cyclical Trend-Upward com/webapps/assessment/take/launch.jsp?course_assessmen
Which of the following time series forecasting methods would not be used to forecast seasonal data? A. dummy variable regression B. simple exponential smoothing C. time series decomposition D. multiplicative Winters method
When deseasonalizing a time series observation, we divide the actual time series observation by its ___________. irregular factor cyclical factor seasonal factor weighted aggregate factor
Time series analysis: is not appropriate for forecasting. is a regression where the independent variable is units of time. is a practical application of multiple regression. All of the above are true.