Descriptive statistics python github

  • How are descriptive statistics calculated?

    To calculate descriptive statistics: Mean: Add up all the scores and divide by the number of scores.
    Mean = (85 + 90 + 75 + 92 + 88 + 79 + 83 + 95 + 87 + 91 + 78 + 86 + 89 + 94 + 82 + 80 + 84 + 93 + 88 + 81) / 20 = 1770 / 20 = 88.5.
    Median: Arrange the scores in ascending order and find the middle value..

  • What do descriptive statistics show?

    Descriptive statistics helps researchers and analysts to describe the central tendency (mean, median, mode), dispersion (range, variance, and standard deviation), and shape of the distribution of a dataset.
    It also involves graphical representation of data to aid visualization and understanding..

Descriptive or summary statistics in python – pandas, can be obtained by using the describe() function. The describe() function gives us the count , mean , standard deviation(std) , minimum , Q1(25%) , median(50%) , Q3(75%) , IQR(Q3 - Q1) and maximum values.

What are descriptive statistics?

Descriptive statistics might seem simple, but they are a daily essential for anlaysts and data scientists

They allow us to summarise data sets quickly with just a couple of numbers, and are in general easy to explain to others

In this post I’ll briefly cover when to use which statistics, and then focus on how to calculate them in Python

What is a Python introduction to statistics?

Introduction to statistics featuring Python

This series of lecture notes aim to walk you through all basic concepts of statistics, such as descriptive statistics, parameter estimations, hypothesis testing, ANOVA and etc

All codes are straightforward to understand


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