Answered: Explain Homoskedasticity-Only Standard…

College Algebra (MindTap Course List)

12th Edition

ISBN:9781305652231

Author:R. David Gustafson, Jeff Hughes

Publisher:R. David Gustafson, Jeff Hughes

Chapter6: Linear Systems

Section6.2: Guassian Elimination And Matrix Methods

Problem 84E: Explain the differences between Gaussian elimination and Gauss-Jordan elimination.

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Explain Homoskedasticity-Only Standard Errors of the covariance matrix?

Definition Definition Measure of how two random variables change together. Covariance indicates the joint variability or the directional relationship between two variables. When two variables change in the same direction (i.e., if they either increase or decrease together), they have a positive covariance. When the change is in opposite directions (i.e., if one increases and the other decreases), the two variables have a a negative covariance.

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One of the assumptions in linear regression is of that the error terms have a constant variance, otherwise known as homoskedasticity. Whereas, the opposite of the mentioned situation, that is, when the error terms do not have a constant variance, the errors are said to be heteroskedastic.

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