F.Abdul Hussein, S. (2016). A Try To Building The Best Linear Regression Model For Prediction And Controlling The Consumption Of Electric Energy In Baghdad. Alustath, 0(49), 485-503.
Sabah F.Abdul Hussein. "A Try To Building The Best Linear Regression Model For Prediction And Controlling The Consumption Of Electric Energy In Baghdad". Alustath, 0, 49, 2016, 485-503.
F.Abdul Hussein, S. (2016). 'A Try To Building The Best Linear Regression Model For Prediction And Controlling The Consumption Of Electric Energy In Baghdad', Alustath, 0(49), pp. 485-503.
F.Abdul Hussein, S. A Try To Building The Best Linear Regression Model For Prediction And Controlling The Consumption Of Electric Energy In Baghdad. Alustath, 2016; 0(49): 485-503.

A Try To Building The Best Linear Regression Model For Prediction And Controlling The Consumption Of Electric Energy In Baghdad

Baghdad College of Economic sciences University
Article 1, Volume 0, Issue 49, October 2018, Pages 485-503
Author
Sabah F.Abdul Hussein
Abstract
This paper tries to build the best linear regression model (BLRM) using Least square method (L.S.M) for data taken from random sample of families in Baghdad to predict and control the local consumption of electric energy. To achieve that aim it has depended on the examination of residuals of linear models. It's used "SPSS system" for the following:
- Detect the outliers and the influential observations of them and also the multicollinearity problem.
- Meet the usual assumptions about the errors (UAE)
- Find the mean square errors (MSE) and the mean square predicted errors (MSPE) as criteria to arrive at BLRM.
Keywords
Key; Words; UAE; Outliers; Multicollinearity; MSE; MSPE
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