which of the following is/are approaches used to forecast demand for a product course hero

by Alexa Lockman 10 min read

Which forecast method will be more responsive to changes in demand?

Hence, the forecast will be more responsive to changes in demand. B. The most frequently used time-series method is exponential smoothing because of its simplicity and the small amount of data needed to support it.

What is the most frequently used time-series forecast method?

A. The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. Hence, the forecast will be more responsive to changes in demand. B. The most frequently used time-series method is exponential smoothing because of its simplicity and the small amount of data needed to support it.

Why is the weighted moving average method used to forecast demand?

The weighted moving average method allows forecasters to emphasize recent demand over earlier demand. Hence, the forecast will be more responsive to changes in demand. B. The most frequently used time-series method is exponential smoothing because of its simplicity and the small amount of data needed to support it.

What type of forecast should be used for manufacturing?

A) Forecasts made in dollars for total sales should be used for manufacturing. B) If we wish to forecast demand, then past sales must be used for the forecast. C) Forecasts should be made for all items, models, and options manufactured.

What are the two aspects of forecasting?

Two aspects of forecasts are important. One is expected level of demand and the other is degree of accuracy. Forecasts that use subjective inputs such as opinions from consumer surveys, sales staff, managers, executives, and experts. -Judgmental forecasts. -Time-series forecasts.

What are predictor variables?

Predictor variables are: -used in regression to predict values of the variable of interest. -variables whose values can be easily determined. -related to the variable of interest. -increasing or decreasing in value over time. 1. Used in regression to predict values of the variable of interest. 2.