Core Statistical Concepts: Statistics & Sampling with Python

Data is one of the most valuable assets a business has but only as valuable as the methods used to interpret it. Data science which at its core includes statistics and sampling is the key to data interpretation. In this course practice using the pandas library in Python to work with statistics and sampling. Practice loading data from a CSV file into a pandas DataFrame. Compute a variety of statistics on data. While doing so see how to visualize the relationship between data and computed statistics. Moving along implement several sampling techniques such as stratified sampling and cluster sampling. Then explore how a balanced sample can be created from an imbalanced dataset using the imblearn module in Python. Upon completion youll be able to generate samples and compute statistics using various tools and methods.