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PRINCIPLES OF MODELLING IN OR.
how to describe association between quantitative and categorical variables
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
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
Procedures for estimating the probability distributions without supposing any particular functional form. Constructing the histogram is perhaps the easiest example of such type of
It is an informal method of assessing the effect of the publication bias, generally in the context of the meta-analysis. The effect measures from each of the reported study are plo
Multi co linearity is the term used in the regression analysis to indicate situations where the explanatory variables are related by a linear function, making the inference of the
Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric max
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
MEANING ,IMPORTANCE AND RELEAVANCE OF SCATTER DIAGRAM
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