Forecast Errors
What does MAD stand for and what does it measure?
Mean Absolute Deviation; average of absolute forecast errors.
What are the four main components of a time series?
Trend, seasonal, cyclical, and irregular.
What is the dependent variable in a simple linear regression?
The variable being predicted (Y).
What is the purpose of multiple regression?
To explain variation in Y using more than one X.
What value of correlation coefficient (r) shows no linear relationship?
Zero (0).
Which error measure penalizes larger errors more heavily than others?
RMSE (Root Mean Squared Error).
Which forecasting method uses weighted averages of past data where weights decrease exponentially?
Exponential Smoothing.
What does the slope coefficient (b1) represent?
Change in Y for each unit change in X.
What problem occurs when independent variables are highly correlated?
Multicollinearity
What’s the range of values the correlation coefficient can take?
-1 to +1.
This error measure expresses forecast accuracy as a percentage, calculated as the average of absolute percentage errors.
MAPE
What is the basic assumption of the naive forecasting method?
The next period’s forecast is equal to the last observed value.
What does a high R-squared indicate?
A strong relationship between X and Y.
What does the Adjusted R-squared account for that R-squared does not?
Number of predictors in the model.
What does autocorrelation analysis typically show if there is trend or seasonality in the data?
Significant autocorrelation at specific lags.
What does a positive MPE indicate?
Forecasts are generally too low (underforecasting).
What is the main limitation of using a moving average model?
It lags behind trends and smooths out sudden changes.
What does the p-value test in regression analysis?
Statistical significance of the coefficients.
What does the Significance F value indicate in a regression output?
The overall significance of the regression model.
Which model helps to forecast the adoption of new products based on innovation and imitation effects?
The Bass Model
What does a Theil’s U value less than 1 indicate about your forecast?
Forecast is better than a naïve forecast.
What does it mean for a time series to be stationary?
Statistical properties like mean and variance are constant over time.
Name two key assumptions of simple linear regression.
Linearity, independence of errors, constant variance, normality of errors.
What is the difference between Significance F and individual p-values in a regression?
Significance F tests the model as a whole; p-values test each individual predictor.
Name “Laws of Forecasting”
1.Forecasts are never totally right, but still useful
2.Forecasts for the near term tend to be more accurate
3.Forecast for groups of products or services tend to be more accurate
4.Don’t forecast if you can avoid it