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Bayesian confidence interval: An interval of the posterior distribution which is so that the density of it at any point inside the interval is greater than that of the density at any point outside and that the area which comes under the curve for that interval is equal to the prespeci?ed probability level. For any probability level there is basically only one such interval, which is also often called as the highest posterior density area. Unlike the usual con?dence interval related with the frequentist inference, here the intervals state the range within which parameters lie with a certain probability.
The initial evaluation of the set of observations to see whether or not they appear to satisfy the hypotheses or assumptions of the methods to be used in their analysis. Techniques
Asymmetric proximity matrices : Proximity matrices in which the non-diagonal elements, in the ith row and jth column and the jth row and ith column, are not essentially equal. Exam
sales per day for a product are as follows: x= 10, 11, 12, 13 (p)= 0.2, 0.4, 0.3, 0.1 obtain mean and variance of daily sale. if the profit is described by the following equation p
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0 i =0, 1, 2, 3
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th
The graphical method for studying the behavior of the seasonal time series. In such a plot, the January values of seasonal component are graphed for the upcoming years, then the
Pie chart is an extensively used graphical technique for presenting relative frequencies related with the observed values of the categorical variable. The chart comprises of a cir
Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo
Kalman filter : A recursive procedure which gives an estimate of the signal when only the 'noisy signal' can be observed. The estimate is efficiently constructed by putting the exp
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