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Median absolute deviation (MAD): It is the very robust estimator of the scale given by the following equation
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.
Information theory: This is the branch of applied probability theory applicable to various communication and signal processing problems in the field of engineering and biology. In
Biplots: It is the multivariate analogue of the scatter plots, which estimates the multivariate distribution of the sample in a few dimensions, typically two and superimpose on th
Ordered alternative hypothesis is a hypothesis or assumption which speci?es an order for the set of parameters of interest as an alternative to the equality, rather than simply th
Prevalence : The measure of the number of people in a population who have a certain disease at a given point in time. It c an be measured by two methods, as point prevalence and p
Q. A toothpaste company want to know if its new product increases the length of time in-between dentist visit to its user. The company sets a target for 180 days to determine if it
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
Confidence profile method : A Bayesian approach to meta-analysis in which the information in each piece of the evidence is captured in the likelihood function which is then used al
Help on my test preparation . .
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
1) Let N1(t) and N2(t) be independent Poisson processes with rates, ?1 and ?2, respectively. Let N (t) = N1(t) + N2(t). a) What is the distribution of the time till the next epoch
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