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Forecasting_Tutorial-4 solutions

Forecasting_Tutorial-4 solutions - Forecasting Tutorial-4...

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Forecasting Tutorial -4 solutions 1. The first step in evaluating a regression model is to determine whether the sign of the estimated slope term makes sense. The second step is to test whether or not the slope term is significantly different from zero. The appropriate statistical test to determine this is a t-test since the true regression error variance is generally unknown. The third check of regression is to evaluate what percent of the variation in the dependent variable is explained by variation in the independent variable. This is given by the R-squared (coefficient of determination) in regression output. Fourth, the regression model should be evaluated for serial correlation. The Durbin-Watson statistic is used in this regard. The problem of serial correlation is common to time-series data and leads to the problem of spurious regression, i.e., misleading regression statistics. 2. Putting the data in graphic form may help the analyst determine patterns in the data such as trend and seasonality.

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Forecasting_Tutorial-4 solutions - Forecasting Tutorial-4...

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