BUSMGT 3230 Quiz 9

there is no historical data due to a new product introduction

Explanation: The judgment methods may be the only practical way to make a forecast when the data are too limited or too scattered to be of any use in making a statistical forecast. In this case, the forecaster must use his or her experience and knowledge to come up with an estimate of what will happen in the future.

delphi method

Explanation: The process of forecasting is a process of gaining consensus from a group of experts. This process is used to generate a forecast for a company or organization. The process typically involves the collection of data from a variety of sources, the development of a forecasting model, and the use of statistical techniques to generate a forecast.

consistent forecasting mistakes - the forecast is always too high or too low

Explanation: A forecast with a large cumulative sum of forecast errors (CFE) indicates that the forecast is not very accurate. The CFE is the sum of the forecast errors for each period in a time series. A large CFE means that the forecast is not very accurate.

FALSE

Explanation: Mean absolute deviation (MAD) is a measure of variability which is computed as the average of the absolute values of the deviations of the data points from their mean. Since the deviations are always either positive or negative, the MAD will be negative if the sum of the deviations is negative.

the forecast has no bias but has a positive standard deviation of errors

Explanation: The forecast method did not accurately predict the actual demand. The forecast errors were found to be:Mean absolute percent error = 10%Cumulative sum of forecast errors = 0This means that, on average, the forecast was off by 10%. Additionally, the cumulative sum of the forecast errors was 0, which means that, on average, the forecast was neither consistently overestimating nor underestimating demand.

Naive forecasting

Explanation: This is an example of the naive forecast method, which simply uses the data from the current period as the forecast for the next period. This is not a very accurate method, but it is simple to implement.

FALSE

Explanation: Judgment methods of forecasting are those that involve using the opinion of experts to make predictions about the future. This could include things like surveys, interviews, and focus groups. Quantitative forecasting methods are those that use historical data and statistical analysis to make predictions.The reason judgment methods should never be used with quantitative forecasting methods is because they are two completely different approaches. Judgment methods are subjective and based on opinions, while quantitative methods are objective and based on data. Using both methods together would not give you an accurate forecast.

FALSE

Explanation: This is because the forecast error is the difference between the actual value and the forecasted value. The cumulative sum of the forecast errors will be positive if the forecasted values are less than the actual values.

TRUE

Explanation: The forecast error is the difference between the forecast demand and the actual demand for a given period. This error can be used to improve future forecasting accuracy.

weighted moving average

Explanation: This forecasting method is called a univariate time series model. This type of model is based on the assumption that the demand at time t+1 can be predicted using only the data on demand at time t-1.