Techniques in AI/ML have made great advances and it is a great exploratory step. But for now, it has not matured enough to reach an inferential step.

The concepts in statistics and mathematics are the building blocks of the techniques and tools we use to gain deeper insights into structured and unstructured data. Statistical concepts lie at the heart of data science.

Read more: https://analyticsindiamag.com/the-role-of-statistics-in-the-era-of-big-data/

Causes of Faulty Statistical Inference: This article discusses the error types and a few important factors that may contribute to the faulty statistical inference

ðŸ”µ Intellipaat Data Analytics course: https://intellipaat.com/data-analytics-master-training-course/In this Statistics Using Excel video, you will learn what...

It generally covers statistics, mathematics, physics, economics, business, and management. Here, weâ€™ll go to different reasons for those undergraduates to learn statistical programming.

Statistical concepts with examples, formula, and python code. The describe() function computes a summary of statistics pertaining to the DataFrame columns. This function gives the mean, std and IQR values. And, function excludes the character columns and given summary about numeric columns.

In this article Iâ€™ll walk you through the terms Descriptive statistics and Inferential statistics. If you wish to check the previous article below is the link.