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Maximum likelihood estimation is an estimation procedure involving maximization of the likelihood or the log-likelihood with respect to the parameters. Such type of estimators is particularly important because of their many desirable statistical properties such as consistency, and asymptotic efficiency. As an example considers the number of successes, X, in a sequence of random variables from a Bernoulli distribution with success probability p. The likelihood can be given by differentiating the log-likelihood, L, with respect to p gives the following
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
Designs which permits two or more questions to be addressed in the investigation. The easiest factorial design is one in which each of the two treatments or interventions are p
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
This is acronym for the Epidemiological, Graphics, Estimation and Testing of the program developed for the analysis of the data from studies in epidemiology. It can be made in use
when there is tie in sequencing then what we do
Generalized poisson distribution: The probability distribution can be defined as follows: The distribution corresponds to the situation in which the values of the rand
The regression analysis is used to fit a model describing the relationship of a dependent variable with independent variable(s). Here we have fitted three regression models:
Randomized response technique : The procedure for collecting the information on sensitive issues by means of the survey, in which an element of chance is introduced as to what quer
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if |t | > t = 1.96
Length-biased sampling : The bias which arises in the sampling scheme based on the visits of patient, when some individuals are more likely to be chosen than others simply because
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