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A sequence of variables in which each variable has a different variance. Heteroscedastics may be used to measure the margin of the error between predicted and actual data.

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Q: What is heteroscedasticity and autocorrelation of the error term?
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Related questions

What is heteroscedasticity?

variables


How can Heteroscedasticity be detected and removed?

There are various tests for heteroscedasticity. For bi-variate data the easiest is simply plotting the data as a scatter graph. If the vertical spread of the data points is broadly the same along its range then the data are homoscedastic and if not then there is evidence of heteroscedasticity. Heteroscedasticity may be removed using data transformations. The appropriate transformation will depend on the data and there is no general transformation that will work in all instances.


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In regression analysis , heteroscedasticity means a situation in which the variance of the dependent variable varies across the data. Heteroscedasticity complicates analysis because many methods in regression analysis are based on an assumption of equal variance.


Are autocorrelation and serial correlation the same?

Yes, they are the same.


What is heteroscedasticity in statistics?

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What is Turbulent Integral Length Scale?

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Unfortunately, there are also some problems with the use of the autocorrelation. Voiced speech is not exactly periodic, which makes the maximum lower than we would expect from a periodic signal. Generally, a maximum is detected by checking the autocorrelation


What is the proper term for mistake?

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Is sometimes the term used for input validation?

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