Doing and discovering statistics using Python programming.
Python functions handling calculating the density, cumulative probability, quantile and random number generation for different statistical distributions: Normal distribution, t distribution, gamma distribution, chi-square distribution, F distribution, beta distribution, Hypothesis testing, etc.
Linear regression and Generalized linear models using Python programming.
ANOVA, factor analysis using Python programming.
Clustering model using Python programming.
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The exponential distribution is modeling the probability distribution of the random time until next event occur in a Poisson event…
Normal distribution is describing random variables with bell-shaped probability density functions. Normal distribution is widely used in data science because…
Poisson distribution is a discrete distribution. It is frequently used to model the counts of event occurrence during a specified…
In hypothesis testing, the possibility of the other side than the conclusion usually exists, and the analysis commits so-called Type…