EDA
Exploratory Data Analysis
This session presents the assumptions, principles, and techniques necessary to gain insight into data via EDA--exploratory data analysis.
we will be covering the essential exploratory techniques for summarizing data. These techniques are typically applied before formal modeling commences and can help inform the development of more complex statistical models. Exploratory techniques are also important for eliminating or sharpening potential hypotheses about the world that can be addressed by the data.
Objectives
Upon completion of the subject, students will be able to:
- Use a variety of basic techniques in understanding and interpreting data;
- Apply elementary statistical methods in analyzing business scenarios and problems;
- Think critically and creatively about the uses and limitations of statistical methods in business;
- Use statistical package and interpret the output, appreciate the applications of information technology for statistical analysis in busines
Module Schedule
-
Day 1: What are Data ? Slides, PDF, Let's Practice, Test you skills, Solution
- Data Science Process
- Discriptive Statistics
-
Day 2: Visulaization Slides, PDF, EDA_Q
-
Day 3:Getting our hand dirty:Pandas and Web Scraping Slides, PDF
-
Day 4: Statistical models Slides, PDF, lets practice, blog on probability distributions
-
Day 5: Story Telling and Effective Communication Slides, PDF