This lesson begins with explaining the multi-variable linear regression method characteristics, and uses. Multi-variable linear regression method attempts to best fit a line through each of the independent variables and the dependent variable. Using an example and the forecasting process, we apply the multi-variable linear regression method method to create a model and forecast based upon it.
14. Multi-Variable Linear Regression Forecasting Steps Set an objective Build model Evaluate model Use model 4 Copyright 2010 DeepThought, Inc.
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16. Multi-linear regression allows to test whether a line through each of the independent variablesworks as a model. Objectives should take that principal under consideration
27. Adds dummy variables for each of the seasons, except for one which is the base season. In our case it will always be the first season such as January for monthly data
76. The lower the T-Test P-Value, the lower the percent that the coefficient is wrongfully assumed to be different from a zero coefficient
77. 1 – p-value = Significance Level of the Coefficient (%)
78. Significance level of the coefficient (%) represents the amount of confidence we have that the coefficient is different from zero14 Copyright 2010 DeepThought, Inc.