bivariate
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metaanalysis projects
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- HTML
Fast streaming univariate and bivariate moments and t-statistics
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- Python
Complex / 2d multivariate bivariate colormap / Domain coloring for Matplotlib, Plotly etc. (pure-numpy)
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- Python
Demonstration of the Gaussian Mixture Model (GMM) for the bivariate normal distribution along with a derivation of the E and M steps.
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- Haskell
Compute a moving sample Pearson product-moment correlation distance incrementally.
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- JavaScript
I Learnt how to make regression for bivariate data in my Statistics class today, So I made a small program to do the same, it takes x and y arrays and outputs a linear equation with slope and constant.
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- Jupyter Notebook
This software package creates subdivision matrices for generalized quadratic and cubic B-spline subdivision for subdivision surfaces as well as subdivision volumes. The subdivision matrices define refinement rules for arbitrary combinatorial structures. The matrices have a valid eigenstructure and a subdominant eigenvalue of 1/2.
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- MATLAB
Compute a sample Pearson product-moment correlation coefficient.
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- JavaScript
Compute a sample Pearson product-moment correlation distance.
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- JavaScript
Compute a moving sample Pearson product-moment correlation coefficient incrementally.
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- JavaScript
Strip Plot, Grouping with Strip Plot, Swarm Plot, Box and Violin Plot, placing plots together, Combining the plots, Joint Plot, Density Plot, Pair Plot
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- Jupyter Notebook
PISA 2012 data visualisation. Univariate, bivariate and multivariate exploration.
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- Jupyter Notebook
Enhance XYZ shop's delivery efficiency by evaluating five delivery services using a comprehensive dashboard to gain insights to improve the selection of delivery service companies.
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Used libraries and functions as follows:
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- Jupyter Notebook
Polynomials are mathematical objects which are expressions of variables and coefficients added to-gether. These polynomials can use operator overloading in a very intuitive manner since most of the operators that we can overload are mathematical operators, which can also be applied to polynomials.
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- C++
Animate Bivariate Normal Distribution using JAX and Matplotlib and making it interactive using ipywidgets.
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- Jupyter Notebook
The analysis focused on segmenting a specific group of mall customers using the KMeans unsupervised machine learning algorithm. Univariate, bivariate, and multivariate clusters were identified and analyzed using summary statistics to gain insights into customer behavior and determine the most valuable segment for targeted marketing strategies.
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- Jupyter Notebook
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