Introduction¶
A probability distribution in statistics is a function that returns the possible values for a variable with different occurence rate (how often values occur). Distribution in nature and society tend to fit pattern with ocasionally occuring exceptions (isn't absence of pattern is a pattern too?).
Probability Mass Function¶
Discrete random variable has probability mass function (PMF) being a particular type of probability distribution read more
Jump In pymc
Install¶
To simply install pymc was not enough on my computer, neither on Google Colab it worked to simply use library after !pip install. Apparently my laptop hadn't a working fortran of C compiler- the message that I got was:
Aesara will be unable to compile C-implementations and will default to Python. Performance may be severely degraded. To remove this warning, set Aesara flags cxx to an empty string.
read more
Bayes Theorem for me
Bayes Theorem¶
Introduction¶
Let us think about probability of a single event - a probability that coin turn up heads for example. Probability (1/2) is the number of outcomes that qualify as event "coin turn up heads" (1) divided by the total number of all possible outcomes (2). To calculate probability of multiple events occuring in sequence we multiply the probabilities of each event in sequence. Consider an event A occuring given that another event B (evidence that B) has occurred - probability of it is known as conditional probability. We need to calculate the probability of A conditinal on event B occuring knowing that probability of B conditional on A occuring. This is the case for applying bayesian inference. What is that? Bayesian inference is a statistical inference that uses Bayes' theorem. It is being applied to geostatistics, genetics, linguistics, image processing, machine learning and other fields.
read moreCorrespondence Analysis
Correspondence Analysis¶
Introduction¶
An introduction to correspondence analysis can be found in the book "Exploratory Multivariate Analysis by Example Using R" by François Husson. It is worth reading and, along with the tutorial series on YouTube tutorial series on YouTube , it is a great source that can help make the basics of correspondence analysis clear to you.
read moreMy First Converted Jupyter notebook
Write Blog Using Jupyter Notebooks and Pelican¶
Here is a quick reviev on how to write blog using Jupyter Notebook and python module pelican-jupyter. Not so much to write about, pelican-jupyter's docs are great. They may be read here: https://github.com/danielfrg/pelican-jupyter.
Pandas Useful Tricks
Introduction¶
Here I want to write a little about pandas that I play with sometimes and share some useful pandas methods. Notice the input data comes from module pydataset that comes with a bunch of popular dataset.