While I try to learn statistics
Python? R? D3Js? SAS?
Step 1:
https://www.khanacademy.org/math/statistics-probability
Udacity learning:
Descriptive Statistics
Notes in the file : Descriptive Statistics
Final project can be found under Descriptive-final-project
Inferential Statistics
Notes in the file: Inferential Statistics
Step 2:
Learn Python for data science:
https://elitedatascience.com/learn-python-for-data-science
1.1: Core Programming concepts
https://docs.python.org/2.7/
https://learnpythonthehardway.org/book/
1.2: Challenges online
1.3: Essential data science libraries
1.3.1: NumPy - NumPy is the grand-daddy of all data science libraries. It allows easy and efficient numeric computation, and many other machine learning libraries are built on top of it.
1.3.2: Pandas - Pandas is high-performance library for data structures and exploratory analysis.
1.3.3: Matplotlib - Flexible plotting and visualization library.
1.3.4: IPython - Interactive shell for Python that makes it much easier to explore data and debug errors. Makes it much more enjoyable to learn Python for data science.
1.3.5: SciPy - Extends NumPy with more functionality, such as calculating integrals, linear algebra, and statistics.