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Prior distributions: The probability distributions which summarize the information about a random variable or parameter known or supposed at a given time instant, prior to attaining further information from the empirical data. It is used almost entirely within the context of Bayesian inference. In any specific study a variety of such kind of distributions might be assumed. For instance, reference priors represent the minimal prior information; clinical priors are used to formalize the opinion of well-informed specific individuals, frequently those taking part in the trial themselves. Lastly, sceptical priors are used when the large treatment differences are considered unlikely.
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
Missing Data - Reasons for screening data In case of any missing data, the researcher needs to conduct tests to ascertain that the pattern of these missing cases is random.
Option-3 scheme is a scheme of measurement used in the situations investigating possible changes over the time in longitudinal data. The scheme is planned to prevent measurement o
We are installing a router for our network. We believe that the time between the arrival of packets will be exponentially distributed with parameter R = 2 packets/second, and th
Graphical deception : Statistical graphics which are not as honest as they should be. It is relatively simple. To mislead the unwary with the graphical material. For instance, c
Healthy worker effect : The occurrence whereby employed individuals tend to have lower mortality rates than those who are unemployed. The effect, which can pose the serious problem
I have a problem I am trying to solve. An oil company thinks that there is a 60% chance that there is oil in the land they own. Before drilling they run a soil test. When there is
Data which occur when failure period is recorded which are dependent. Such type of data can arise in number contexts, for instance, in epidemiological cohort studies in which th
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
The Null Hypothesis - H0: There is no autocorrelation The Alternative Hypothesis - H1: There is at least first order autocorrelation Rejection Criteria: Reject H0 if LBQ1 >
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