Why Statistics ?
Statistics is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data. It is regarded as one of the pillars of data science and machine learning.
Why Python ?
Python is a general purpose programming language. It's very easy to understand. Also, you can use python for developing complex scientific and numeric application. Python is designed with features to facilitate data analysis and visualization.
What to expect further ?
I will cover topics on python along with statistics using examples.
Major topics to be covered :
1. An Introduction - Setting Up your programming environment
2. Python Basics - Fundamentals of Libraries, Data Types, Math Operations, Exceptions, I/O, OOP
3. Numpy - To perform operations on arrays and matrices
4. Pandas - Performing Data Manipulation
5. Matplotlib : Performing Data Visualization
6. Measures of Central Tendency
7. Measures of Variation
8. Measures of Skewness, Kurtosis and Moments
9. Sampling and Sampling Distributions
10. Univariate Statistics
11. Multivariate Statistics
12. Dimension Reduction and Feature Extraction
13. Clustering
14. Linear Method for Regression
15.Classification
Application of "Statistics Using Python In Real Life"
1. Direct Marketing
2. Online Advertising
3. Credit Scoring
4. Financial Trading
5. Fraud Detection
6. Search Ranking
7. Product Recommendation
