Data Science in Health Care. Basic statistical analysis.
Learn basic statistical analysis for data science in healthcare. Explore techniques to analyze and interpret healthcare data for improving patient outcomes and decision-making processes.
At a Glance
ELISA is a commonly used laboratory test to detect antibodies in the blood. An antibody is a protein produced by the body’s immune system when it detects harmful substances, called antigens. In this project you will learn how to download, prepare and make statistical analysis of ELISA tests and collected information about IgG and IgM, vaccination influenza, vaccination tuberculosis and other diseases and blood groups.
This project will give you a practical introduction to basics of analyzing ELISA test data using readily available data science tools. You will download a real ELISA dataset, prepare it for statistical analysis, and analysis of information about IgG and IgM antibodies as they apply to the influenza and tuberculosis vaccination.
Learning Objectives
After completing this project you will be able to:
- Download test datasets (Excel files .xlsx) to use them in Python
- Automatically clean and prepare data in dataset
- Transform the table
- Visualize data with Pandas and Seaborn, two very popular data analysis and visualization libraries
You will be able to create basic statistical analysis of the ELISA data deriving:
- Minimum and maximum values
- Averages
- Quarters
- and create pivot tables
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