Python package containing functions implemented for descriptive and inferential statistics.

The objective of this work is to provide tools to be used for the classification of ordinal categorical distributions. To demonstrate how to do it, we propose an Homogeneity (HI) and Location (LI) Index to measure the concentration and central value of an ordinal categorical distribution.

Basic Statistic operations using R language

Calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm with extended accumulation and returning an extended precision result.

Calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.

Calculate the mean and variance of a double-precision floating-point strided array.

Calculate the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm with pairwise summation.

Calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation with extended accumulation and returning an extended precision result.

Calculate the arithmetic mean of a single-precision floating-point strided array, ignoring NaN values.

Compute a moving geometric mean incrementally.

Business Analyst Portfolio

Calculate the arithmetic mean of a double-precision floating-point strided array using a two-pass error correction algorithm.

Calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.

Calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring NaN values.

Data Analysis Course (EE 201), IIT Dharwad

Create an iterator which iteratively computes a moving mid-range.

Compute a mid-range incrementally.

Compute a harmonic mean incrementally.

Compute a corrected sample standard deviation incrementally.

Compute an unbiased sample variance incrementally.