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Contour plot: A topographical map drawn from data comprising observations on the three variables. One variable is represented on horizontal axis and the second variable is represented on the vertical axis. The third variable is represented by the isolines. These plots are many times helpful in data analysis, especially when the searching for maxima or minima in such type of data. The plots are most often taken in use to display the graphically bivariate distributions in which case the third variable is value of the probability density function corresponding to the values of the two variables. An alternative method or technique of displaying the same material is given by the perspective plot in which the values on third variable are represented by the series of lines constructed to give the three-dimensional view of data. The figure 43 drawn above gives examples of these plots using the birth and death rate data from the number of nations with a kernel density estimator used to calculate or measure the bivariate distribution.
Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is
The skewness is a measure of asymmetry and as it is positive at 4.29, it is greater than zero which reveals that the tail extends to the right indicating the distribution to be mor
data modelling
Randomization tests are the procedures for determining the statistical significance directly from the data with- out recourse to some particular sampling distribution. For instanc
difference between histogram and historigram
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
the problem that demonstrates inference from two dependent samples uses hypothetical data from TB vaccinations and the number of new cases before and after vaccinations for cases o
ain why the simulated result doesn''t have to be exact as the theoretical calculation
Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past
Technically the multivariate analogue of the quasi-likelihood with the same feature that it leads to consistent inferences about the mean responses without needing specific supposi
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