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Randomization tests are the procedures for determining the statistical significance directly from the data with- out recourse to some particular sampling distribution. For instance, in a study including the comparison of two groups, the data would be splittes (permuted) repeatedly between groups and for each split (permutation) the relevant test statistic (for instance, a t or F), is calculated to determine the proportion of data permutations which provide as large a test statistic as that associated with observed data. If that quantity is smaller than some significance level α, the results are important at the α level.
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
Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu
Institutional surveys are the surveys in which the primary sampling units are the institutions, for instance, hospitals. Within each of the sampled institution, a sample of the pa
how to resolve sequencing problem if jobs 6 given and 4 machines given. how to apply johnson rule for making to machines under this conditions. please give solution as soon as poss
The rapid development or growth of the disease in a community or region. Statistical thinking has made very much significant contributions to the understanding of such type of phen
The function of a variable t which, when extended formally as a power series in t, yields factorial moments as the coefficients of the respective powers. If the P(t) is probability
Multivariate data is the data for which each observation consists of the values for more than one random variable. For instance, measurements on the blood pressure, temperature an
The special cases of the probability distributions in which the random variable's distribution is concentrated at one point only. For instance, a discrete uniform distribution when
Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
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
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