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Bootstrap: The data-based simulation method/technique for the statistical inference which can be used to study the variability of the estimated characteristics of the probability distribution of a set of observations and give con?dence intervals for the parameters in situations where these are difficult or impossible to derive in the usual manner. (The use of term bootstrap derives from the phrase 'to pull oneself up by the one's bootstraps'.) The general idea and approach of the procedure involves sampling with the replacement to produce random samples of size n from the original data, x1; x2; ... ; xn; each of these is called as a bootstrap sample and each gives an approximate idea of the parameter of interest. Repeating the process the large number of times provides the desired information on the variability of the estimator and the approximate 95% con?dence interval can, for instance, be derived from the 2.5% and 97.5% quantiles of the replicate values.
Case-cohort study : The research design in epidemiology which involves the sampling of controls at the outset of the study that is to be compared with the cases from the cohort. Th
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
What is statistical inference? Statistical inference can be defined as the method of drawing conclusions from data which are subject to random variations. This is based o
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
The Null Hypothesis - H0: Model does not fit the data i.e. all slopes are equal to zero β 1 =β 2 =...=β k = 0 The Alternative Hypothesis - H1: Model does fit the data i.e. at
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
Bivariate survival data : The data in which the two related survival times are of interest. For instance, in familial studies of disease incidence, data might be available on the a
Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical
A unified approach to all problems of prediction, estimation, and hypothesis testing. It is based on concept of the decision function, which tells the performer of experiment how t
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