How to Calculate Central Tendency and Asymmetry measures in Statistics and Python

How to Calculate Central Tendency and Asymmetry measures in Statistics and Python

In this blog, I am going to talk about Central Tendency, asymmetry and variability with hands on using Python

In this blog, I am going to talk about Central Tendency, asymmetry and variability with hands on using Python. If you miss my previous blog about Descriptive Statistics with Python, please go to the below link.https://medium.com/analytics-vidhya/descriptive-statistics-with-python-part-1-9f34e48abc05

What is Central Tendency? : In statistics, a central tendency is a central or typical value for a probability distribution.

Purpose of Central Tendency: It is a single value which is the representative of an entire distributed data. There are three main measures in central tendency, mean, median and mode.

Now we are going to in detail to know about these measures.

Mean: Mean is mostly used for measuring central tendency. It is a simple average of whole data set. Formula of calculating mean of a data set is

(𝑥1 + 𝑥2 + 𝑥3 + ⋯ + 𝑥𝑁−1 + 𝑥𝑁 ) /N

Where 𝑥1, 𝑥2 , 𝑥3 , ⋯ ,𝑥𝑁−1 , 𝑥𝑁 => r Data values , N = Total number of sample data.

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For population data, it is denoted as μ and for sample data x bar (symbol shown in above image)

Note: Mean is easily affected by outliers.

Mean Example: Find out Mean explanation with some example.

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