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Bivariate boxplot: A bivariate analogue of boxplot in which the inner area contains 50%of the data, and a 'fence' helps to identify the potential outliers. Robust methods or techniques are usually used to ?nd out the estimates of the location, scale and correlation parameters needed to construct the plot, so as to avoid possible distortions which outlying observations might cause. An instance of such a plot for number of manufacturing enterprises and sulphur dioxide concentration recorded for the number of cities in USA with cities deemed outliers labeled with the name of city.
Intention-to-treat analysis is the process in which all the patients randomly allocated to a treatment in the clinical trial are analyzed together as representing that particular
CONSTRUCTION OF AN OR MODEL
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approac
Reasons for screening data Garbage in-garbage out Missing data a. Amount of missing data is less crucial than the pattern of it. If randomly
Prevented fraction is a measure which can be used to attribute the protection against the disease directly to an intervention. The measure can given by the proportion of disease w
Case-control study : The traditional case-control study is the common research design in the epidemiology where the exposures to risk factors for cases (individuals getting the dis
Poisson regression In case of Poisson regression we use ηi = g(µi) = log(µi) and a variance V ar(Yi) = φµi. The case φ = 1 corresponds to standard Poisson model. Poisson regre
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