Statistical Analysis
Learn Statistical methods to collect data, employ correct analysis, and present results. Enroll in the course to understand descriptive statistical and exploratory analysis to identify patterns and trends for free online!
What you learn in Statistical Analysis ?
About this Course
The Statistical Analysis course is designed to help you understand how to employ statistical methods to hoard data, employ analytical techniques, and effective ways to present results. The course begins with explaining the descriptive statistical analysis and then continues with different concepts in exploratory analysis. It also comprehends a demonstration of an insurance company to help you understand the overall subject better. Take up the quiz at the end of the course and avail your free certificate. You can also refer to the attached materials at any point after enrolling in the course.
After completing this free, self-paced, beginner's guide to Statistical Analysis, you can embark on your Data Science career with a professional Post-Graduate Data Science certificate course and learn various concepts with millions of aspirants across the globe!
Course Outline
This section begins with explaining what descriptive analysis is and then briefs about its process followed in any business or an organization, including the measure of frequency, the measure of central tendency, the measure of variance, and the measure of position.
This section explains exploratory analysis, a business intelligence tool, different challenges an organization faces, data pre-processing, visualization creation, and defines different KPIs with a real-time example.
This section explains the problem statement of a medical insurance company, the different challenges it faces, and the different data categories under the dataset to apply and solve through statistical analysis.
This section begins by explaining what the Jupyter notebook is used for. It solves the fraudulent of the previously understood problem on a medical insurance company by employing statistical analysis using the Jupyter notebook.
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1.0 Hours
of self-paced video lectures
