trend
For data with ___, the naive forecast is equal to the last value of the series plus or minus the difference between the last two values of the series. For example, suppose the last two values were 50 and 53. The next forecast would be 56
white noise
Random unpredictable variations within data are sometimes called ___ ___.
Averaging
___ techniques (Moving average, Weighted moving average, Exponential smoothing) generate forecasts that reflect recent values of a time series (e.g., the average value over the last several periods).
naive
One weakness of the ___ method is that the forecast just traces the actual data, with a lag of one period; it does not smooth at all.
moving average
A ___ ___ forecast uses a number of the most recent actual data values in generating a forecast
moving
In a ___ average the forecast is updated by adding the newest value and dropping the oldest and then recomputing the average. Consequently, the forecast "moves" by reflecting only the most recent values.
sensitive (responsive)
The fewer the data points in an average, the more ___ the average tends to be.
lag
The more periods in a moving average, the greater the forecast will ___ changes in the data.
weighted
A ___ average is similar to a moving average, except that it typically assigns more weight to the most recent values in a time series.
Exponential smoothing
A weighted averaging method where each new forecast is based on the previous forecast plus a percentage of the difference between that forecast and the actual value of the series at that point.
less
In exponential smoothing the closer the value of α is to 1.00, the greater the responsiveness and the ___ the smoothing.
trend-adjusted exponential smoothing
A variation of simple exponential smoothing used when a time series exhibits a linear trend.
additive
In the ___ model, seasonality is expressed as a quantity, which is added to or subtracted from the series average in order to incorporate seasonality.
multiplicative
In the ___ model, seasonality is expressed as a percentage of the average (or trend) amount, which is then used to multiply the value of a series to incorporate seasonality.
20
Suppose that the seasonal relative for the quantity of toys sold in May at a store is 1.20. This indicates that toy sales for that month are __% above the monthly average.
deseasonalize
Seasonal relatives are used in two different ways in forecasting: to ___ data; to incorporate seasonality in a forecast.
centered moving average
a moving average positioned at the center of the data that were used to compute it
Cycles
___ are up-and-down movements similar to seasonal variations but of longer duration—say, two to six years between peaks.
leading
Changes in the ___ variable precede changes in the variable of interest.
Regression
Technique for fitting a line to a set of points.
Predictor
Variables that can be used to predict values of the variable of interest.
Least squares line
Form of regression that minimizes the sum of the squared vertical deviations around the line.
Standard error of estimate
A measure of the scatter of points around a regression line.
Correlation
___ measures the strength and direction of relationship between two variables.
0
A correlation close to __ indicates little linear relationship between two variables.
random variation
Use of simple regression analysis implies that certain assumptions have been satisfied: ___ ___ ; normal distribution; Predictions are being made only within the range of observed values.
normal distribution
Use of simple regression analysis implies that certain assumptions have been satisfied: random variation; ___ ___; Predictions are being made only within the range of observed values.
range observed
Use of simple regression analysis implies that certain assumptions have been satisfied: random variation; normal distribution; Predictions are being made only within the ___ of ___ values.
one
A weakness of simple linear regression is it applies only to linear relationships with ___ independent variable.
data
A weakness of regression is needing a considerable amount of ___ to establish the relationship—in practice, 20 or more observations.
equally
A weakness of regression is all observations are weighted ___.
historical
Several of the qualitative techniques are well suited to long-range forecasts because they do not require ___ data.
reactive
A ___ approach views forecasts as probable future demand, and a manager reacts to meet that demand.
proactive
A ___ approach seeks to actively influence demand (e.g., by means of advertising, pricing, or product/service changes).
credibility
Better short-term forecasts will not only enhance profits through lower inventory levels, fewer shortages, and improved customer service, they also will enhance forecasting ___ throughout the organization.
accurate
Forecasts that cover shorter time frames tend to be more ___ than longer-term forecasts.
Lean
___ systems are demand driven, they are far less dependent on short-term forecasts than more traditional systems
efficiency performance
Commonly used criteria in assignment models include: costs, profits, ___, and ___.
Assignment
A special-purpose linear programming model for optimal assignment of tasks or other work requirements to resources: assigning jobs to machines or workers, territories to salespeople, and repair jobs to repair crews.
backlog
A key portion of an input/output report for a work center is the ___ of work waiting to be processed; also reveals deviations-from-planned for both inputs and outputs
Input/output (I/O)
___ control: Managing and monitoring work flow and queues at work centers to keep them in control.
update costs times
Gantt charts possess certain limitations: the need to repeatedly ___ to keep current; does not directly reveal ___ associated with alternative loadings; complexity of variations in work centers' processing ___
