Explain median absolute deviation (mad), Advanced Statistics

Assignment Help:

Median absolute deviation (MAD): It is the very robust estimator of the scale given by the following equation

1368_MAD.png 
or, in other words we can say that, the median of the absolute deviations from the median of data. In order to use MAD as the consistent estimator of the standard deviation it is multiplied by a scale factor which depends on the distribution of the data. For normally distributed data the constant is 1.4826 and expected value of 1.4826 MAD is approximately equal to population standard deviation.


Related Discussions:- Explain median absolute deviation (mad)

Conjugate prior, Conjugate prior : The distribution for samples from the pa...

Conjugate prior : The distribution for samples from the particular probability distribution such that the posterior distribution at each stage of the sampling is of the identical f

Indirect standardization, Indirect standardization is the procedure of adju...

Indirect standardization is the procedure of adjusting the crude mortality or morbidity rate for one or more variables by making use of a known reference population. It may, for in

Coefficient of concordance, Coefficient of concordance : The coef?cient is ...

Coefficient of concordance : The coef?cient is taken in use to assess the agreement among m raters ranking n individuals according to some of the speci?c characteristic. Which can

Decision theory, A unified approach to all problems of prediction, estimati...

A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t

Conjoint analysis, Conjoint analysis : The method used basically in market ...

Conjoint analysis : The method used basically in market research which is similar in many respects to the various dimensional scaling. The method attempts to assign values to the l

Tests for heteroscedasticity, Lagrange Multiplier (LM) test The Null Hy...

Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1:  There is heteroscedasticity i.e. β 1

Explain johnson-neyman technique, Johnson-Neyman technique:  The technique ...

Johnson-Neyman technique:  The technique which can be used in the situations where analysis of the covariance is not valid because of the heterogeneity of slopes. With this method

Adjusted r-squared, R-squared is regarded as the coefficient of determinati...

R-squared is regarded as the coefficient of determination and is used to give the proportion of the fluctuation of the variance of one variable to another variable. R-squared also

Collapsing categories, Collapsing categories : A procedure generally applie...

Collapsing categories : A procedure generally applied to contingency tables in which the two or more row or column categories are combined, in number of cases so as to yield the re

Mba, Mention the characteristics of Statistics. Explain any two application...

Mention the characteristics of Statistics. Explain any two applications of Statistics.

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd