Dr. Ahmed G. Abo-Khalil

Electrical Engineering Department

Ordinary least squ

In statistics, ordinary least squares (OLS) or linear least squares is a method for estimating the unknown parameters in a linear regression model. This method minimizes the sum of squared vertical distances between the observed responses in the dataset and the responses predicted by the linear approximation. The resulting estimator can be expressed by a simple formula, especially in the case of a single regressor on the right-hand side.

The OLS estimator is consistent when the regressors are exogenous and there is no perfect multicollinearity, and optimal in the class of linear unbiased estimators when the errors are homoscedastic and serially uncorrelated. Under these conditions, the method of OLS provides minimum-variance mean-unbiased estimation when the errors have finite variances. Under the additional assumption that the errors be normally distributed, OLS is the maximum likelihood estimator. OLS is used in economics (econometrics), Political Science and electrical engineering (control theory and signal processing), among many areas of application.

Office Hours

Monday 10 -2

Tuesday 10-12

Thursday 11-1

My Timetable


Contacts


email: [email protected]

[email protected]

Phone: 2570

Welcome

Welcome To Faculty of Engineering

Almajmaah University


IEEE


http://www.ieee.org/

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Links of Interest


http://www.utk.edu/research/

http://science.doe.gov/grants/index.asp

http://www1.eere.energy.gov/vehiclesandfuels/

http://www.eere.energy.gov/


Travel Web Sites

http://www.hotels.com/

http://www.orbitz.com/

http://www.hotwire.com/us/index.jsp

http://www.kayak.com/

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