OPMA CH 3 Forecasting
In business forecasting, what is usually considered a long-term time period?
2 years or longer
In business forecasting, what is usually considered a medium-term time period?
3 months - 2 years
If a firm produced a standard item with relatively stable demand. the smoothing constant alpha (reaction rate to differences) used in an exponential smoothing forecast model would tend to be in which of the following ranges?
5% to 10%
Heavy sales of umbrellas during a rain storm is an example of which of the following?
A casual relationship
In most cases, demand for products or services can be broken into several components. Which of the following is considered a component of demand?
Autocorrelation
In most cases, demand for products or services can be broken into several components. Which of the following is considered a component of demand?
Cyclical elements
Which of the following forecasting methods is very dependent on selection of the right individuals who will judgmentally be used to actually generate the forecast?
Delphi method
Which of the following is a possible source of bias error in forecasting?
Failing to include the right variables
A central premise of exponential smoothing is that more recent data is less indicative of the future than data from the distant past (T/F)
False
A good forecaster is one who develops special skills and experience at one forecasting technique and is capable of applying it to widely diverse situations (T/F)
False
Bayesian analysis is the simplest way to choose weights for the weighted moving average forecasting model (T/F)
False
Continual review and updating in light of new data is a forecasting technique called second-guessing (T/F)
False
Cyclical influences on demand are often expressed graphically as line (T/F)
False
Exponential smoothing is always the best and most accurate of all forecasting models (T/F)
False
For every forecasting problem there is one best forecasting technique (T/F)
False
In casual relationship forecasting leading indicators are used to forecast occurrences (T/F)
False
In decomposition of time series data it is relatively easy to identify cycles and auto-correlation components (T/F)
False
In the simple exponential smoothing forecast model you need at least 30 observations to set the smoothing constant alpha (T/F)
False
In the weighted moving average forecasting model the weights must add up to one times the number of data points (T/F)
False
It is difficult to identify the trend in time series data (T/F)
False
Linear regression is not useful for aggregate planning (T/F)
False
Market research is a quantitative method of forecasting (T/F)
False
Multiple regression analysis uses several regression models to generate a forecast (T/F)
False
Qualitative forecasting techniques generally take advantage of the knowledge of experts and therefore do not require much judgment (T/F)
False
RSFE stands for "reliable safety function error" (T/F)
False
Random errors in forecasting occur when an undetected secular trend is not included in a forecasting model (T/F)
False
The equation for exponential smoothing states that the new forecast is equal to the old forecast plus the error of the old forecast (T/F)
False
The standard error of the estimate of a linear regression is not useful for judging the fit between the data and the regression line when doing forecasts (T/F)
False
There are no differences in strategic and tactical forecasting. A forecast is a mathematical projection and its ultimate purpose should make no difference to the analyst (T/F)
False
Trend lines are usually the last things considered when developing a forecast. (T/F)
False
We usually associate the word "seasonal" with recurrent periods of repetitive activity that happen on other than an annual cycle (T/F)
False
When forecast errors occur in a normally distributed pattern, the ratio of the mean absolute deviation to the standard deviation is 2 to 1, or 2 x MAD = 1 standard deviation (T/F)
False
Which of the following is not one of the basic types of forecasting?
Force field analysis
In business forecasting, what is usually considered a short-term time period?
Less than 3 months
Which of the following forecasting methodologies is considered a casual forecasting technique?
Linear regression
In general, which forecasting time frame is best to detect general trends?
Long range forecasts
Which of the following forecasting methodologies is considered a qualitative forecasting technique?
Market research
Which of the following are used to describe the degree of error?
Mean absolute deviation
In general, which forecasting time frame best identifies seasonal effects?
Medium term forecasts
Which of the following forecasting methods uses executive judgement as its primary component for forecasting?
Panel consensus
In most cases, demand for products or services can be broken down into several components. Which of the following is not considered a component of demand?
Past data
Which of the following considerations is not a factor in deciding which forecasting model a firm should choose?
Product
In general, which forecasting time frame compensates most effectively for random variation and short term changes?
Short term forecasts
Which of the following forecasting methods can be used for short-term forecasting?
Simple exponential smoothing
Which of the following forecasting methodologies is considered a time series forecasting technique?
Simple moving average
A company has a MAD of 10. It wants to have a 99.7 percent control limits on its forecasting system. It's most recent tracking signal value is 3.1. What can the company conclude from this info?
The forecasting model is operating acceptably
If a firm produced a product that was experiencing growth in demand, the smoothing constant alpha (reaction rate to differences) used in an exponential smoothing forecasting model would tend to be which of the following?
The more rapid the growth, the higher the percentage
The exponential smoothing method requires which of the following data to forecast the future?
The most recent forecast
A restriction in using linear regression is that it assumes that past data and future projections fall on or near a straight line (T/F)
True
A time series is defined in the text as chronologically ordered data that may contain one or more components of demand variation: trend, seasonal, cyclical, auto-correlation, and random (T/F)
True
A tracking signal (TS) can be calculated using the arithmetic sum of forecast deviations divided by the MAD (T/F)
True
Because the factors governing demand for products are very complex, all forecasts of demand contain error (T/F)
True
Cyclical influences on demand may come from occurrences such as political elections, war or economic conditions. (T/F)
True
Decomposition of a time series means identifying and separating the time series data into its components (T/F)
True
Experience and trial and error are the simplest ways to choose weights for the weighted moving average forecast model (T/F)
True
Exponential smoothing forecasts always lag behind the actual occurrence but can be corrected somewhat with a trend adjustment (T/F)
True
In a forecasting model using simple exponential smoothing the data pattern should remain stationary (T/F)
True
In a forecasting model using simple moving average, the shorter the time span used for calculating the moving average, the closer the average follows volatile trends (T/F)
True
In exponential smoothing, it is desirable to use a higher smoothing constant when forecasting demand for a product experiencing high growth (T/F)
True
MAD statistics can be used to generate tracking signals (T/F)
True
RSFE stands for "running sum of forecast errors" (T/F)
True
Random errors can be defined as those that cannot be explained by the forecast model being used (T/F)
True
Regression is a functional relationship between two or more correlated variables, when one variable is used to predict another (T/F)
True
Simple exponential smoothing lags changes in demand (T/F)
True
The value of the smoothing constant alpha in an exponential smoothing model is between 0 and 1 (T/F)
True
The weighted moving average forecasting model uses a weighting scheme to modify the effects of individual data points. This is its major advantage over the simple moving average model (T/F)
True
Time series forecasting models make predictions about the future based on analysis of past data. (T/F)
True
In time series data depicting demand which of the following is not considered a component of demand variation?
Variance
Which of the following forecasting methodologies is considered a time series forecasting technique?
Weighted moving average
