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The analysis of data which are the functions observed continuously, for instance, functions of time. Basically a collection of statistical techniques or methods for answering questions like 'in what manner do the curves in the sample differ?', using information on the curves like slopes and curvature.
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The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
Can I use ICC for this kind of data? Wind Month Day Temp(DV) 7.4 5 1 67 8 5 2 72 12.6 5 3 74 11.5 5 4 62 I am taking temp as the dependent variable. There are many more values.
Bayesian inference : An approach to the inference based largely on Bayes' Theorem and comprising of the below stated principal steps: (1) Obtain the likelihood, f x q describing
The equation linking the height and weight of the children between the ages of 5 and 13 and given as follows here w is the mean weight in kilograms and h the mean height in
The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio
A rule for computing the number of classes to use while constructing a histogram and can be given by here n is the sample size and ^ γ is the estimate of kurtosis.
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
I want to get the quotation of my on-line assignment its based on 1000 words. lecturer provide the video links and we have to watch the videos and highlights the key points also de
Conditional probability : The probability that an event occurs given the outcome of other event. Generally written, Pr(A|B). For instance, the probability of a person being color b
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