Tag Archives: Numpy

Fooled by probability – Monty Hall Problem

“You made a mistake, but look at the positive side. If all those Ph.D.’s were wrong, the country would be in some very serious trouble.” Everett Harman, Ph.D. U.S. Army Research Institute Probability is a terrible branch of science, I … Continue reading

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A great tutorial on the FFT using Python, Numpy,Scipy & Matplotlib

Great FFT tutorial from Real Python

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Fast Fourier Transform – An Intuition

One of my favorite youtube channels, 3Blue1Brown, has a great video on the intuition of the FFT. Check the video above. Below Python code to implement that intuition:

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Python Pandas – descriptive stats from a frequency table

Suppose you are a teacher, and want to keep track of and do some simple descriptive stats on your student’s scores in a number of subjects. So you have recorded scores in a frequency table as below: Left-most column has … Continue reading

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Corona : slowing down…?

Some further analysis on Corona, with data up and including yesterday. First, let’s look at the global spread: The first of these plots has linear (lin/lin) scale, and should be familiar from any of the many sites that post data … Continue reading

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Tour de Ski Final climb – does age matter for performance ?

In an earlier post, I analyzed data from the Marcialonga Ski race. Marcialonga is one of the classic long distance ski races, where both elite’ as well as amateurs compete together. In fact, the vast majority of the competitors in … Continue reading

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Marcialonga Ski 2019 – some Analytics

Now, with the power grid finally – after 62 hours! – back in business, I’m able to continue my stats/analytics exploration of the past Marcialonga ski race. First, some basic stats about the race: Total number of participants: 5558, of … Continue reading

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Bayesian Linear Regression with PYMC

Python, Pandas & PYMC example on Bayesian Linear Regression, adopted from Richard McElreath’s “Statistical Rethinking” class, where he uses R as modeling language instead of PYMC. Data in a csv-file describe various attributes such as weight, height, age, gender etc … Continue reading

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Python & Pandas to map gps coordinates to known locations

Assume you have a gps log file, with time and position (Lat,Lon in columns 9,10) info, like: 2018.12.12 00:41:20;0;0;0;0;0;1;0;25.8;59.348978;17.969643;0;0; 2018.12.12 01:41:21;0;0;0;0;0;1;0;25.7;59.348962;17.969627;0;0; 2018.12.12 02:41:21;0;0;0;0;0;1;0;25.7;59.349;17.969688;0;0; 2018.12.12 03:41:21;0;0;0;0;0;1;0;25.7;59.349;17.96966;0;0; 2018.12.12 04:41:22;0;0;0;0;0;1;0;25.6;59.349007;17.969618;0;0; 2018.12.12 04:48:50;0;0;0;0;1;1;1;25.2;59.349007;17.969635;0;0; 2018.12.12 04:49:51;0;0.001;0;0;1;1;1;28.3;59.349;17.969642;0;0; Assume further that you’d like to map each of … Continue reading

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Using Bayesian Inference to predict and bet on Italian Serie A Fotball

As my old timer readers know, I’be been using Bayesian Inference to predict and bet on various sporting events, such as FIFA World Cup, and IIHF World Championships. With some success. When the Italian premier division started for about a … Continue reading

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