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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.
Command-Line options Compression: C++: ./compress -f myfile.txt [-o myfile.hzip -s Java: sh compress.sh -f myfile.txt [-o myfile.hzip -s] Decompression:
Compliance : The extent to which the participants in a clinical trial follow trial protocol, for instance, following both the intervention regimen and trial procedures (clinical vi
Censored observations : An observation xi on some variable of interest is consired to be censored if it is known that xi Li (left-censored)or xi Ui (right-censored) where Li and Ui
Likelihood is the probability of a set of observations provided the value of some parameter or the set of parameters. For instance, the likelihood of the random sample of n observ
Interval-censored observations are the observations which often occur in the context of studies of time elapsed to the particular event when subjects are not monitored regularl
The Null Hypothesis - H0: There is no first order autocorrelation The Alternative Hypothesis - H1: There is first order autocorrelation Durbin-Watson statistic = 1.98307
Intercropping experiments are the experiments including growing two or more crops at same time on the same patch of land. The crops are not required to be planted nor harvested at
Multiple imputation : The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simula
data modelling
A directed graph is simple if each ordered pair of vertices is the head and tail of at most one edge; one loop may be present at each vertex. For each n ≥ 1, prove or disprove the
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