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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 regression coefficients impossible. Including the sum of explanatory variables in the regression analysis would, for instance, lead to this problem. Estimated multi co linearity can also cause problems while estimating regression coefficients. In particular if multiple correlations for the regression of the particular explanatory variable on the others is high, then the variance of corresponding estimated regression coefficient will also be quite high.
Q. A toothpaste company want to know if its new product increases the length of time in-between dentist visit to its user. The company sets a target for 180 days to determine if it
This is the theorem which states that if the error terms in a multiple regression have the same variance and are not corrected, then the estimators of the parameters in the model p
A term usually used for unobserved individual heterogeneity. Such variation is of main concern in the medical statistics particularly in the analysis of the survival times where ha
This term is sometimes used for the analysis of data from the clinical trial in which treatments A and B are to be compared under the suppositions that the patients remain on their
Coincidences : Astonishing concurrence of the events, perceived as meaningfully related, with no apparent causal connection. Such type of events abounds in everyday life and is oft
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
Difference between tretment design and experimental design
The probability distribution of the various observations is required to obtain the run of two successes in the series of Bernoulli trials with the probability of success equal to a
Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the
Hurdle Model: The model for count data which postulates two processes, one generating the zeros in the data and one generating positive values. The binomial model decides the bina
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