Monthly Archives: January 2016

Chi-square distribution and degrees of freedom

Chi-square test is the goodness of fit between a set (or vector) of observed values and expected values. Chi-square is one among other distributions. Typical chi-square distribution can be plotted with following R code: x = seq(0, 30, length.out =

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Playing with Regression prediction and MSE measure

In previous post, I have discussed on how to create a sample data-set in R. So let’s use the created data-set from previous post and start playing with Regression predictions. With each prediction we want to measure, which one scores

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Random permutations and t-test

Let’s assume that we have two groups (= datasets) of observations. And we are interested if two sets of data are significantly different from each other. In first place we will compare the means of each group and for these

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Generating sample data in R

When testing random functions or predictions in R it is usually a good thing to have some sample or random data. A lot of libraries and base libraries in R are equipped with good sample data, but let me show

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