nirupamaprv / Practical_Stats

Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems

Practical_Stats

Exercises solved for the Practical Statistics Module of Udacity's DAND: assignments and practice problems

Overview and Structure

• The content here is from studying Udacity's Data Analyst Nano Degree [DAND] Term 1 course.
• Notes taken during lectures are in .docx files
• .ipynb files are the coding exercises accomplished as part of the curriculum.
• Files in .pynb format are in Python 3, coded using either Udacity's in-course workspace or Anaconda Navigator. These files also include Markdown cells.

.ipynb File Overview

• "Central Limit Theorem.ipynb", "Central Limit Theorem - Part II.ipynb" and "Central Limit Theorem - Part III.ipynb" explain concept of Central Limit Theorem via code
• "Law of Large Numbers.ipynb" reinforces topic of Law of Large Numbers using numPy and matplotlib packages
• "conditional_probability_bayes_rule.ipynb" is evaluation of Cancer dataset. We compute Conditional probabilities of having cancer or not and False Positives
• "simpsons_paradox.ipynb" - Here, we work with Admissions Dataset to calculate proportions of majors, majors for each gender as well as acceptance rates by gender and by major.
• "simulating_coin_flips.ipynb" - Coin Flips are computed in this file using NumPy. We get to view how actual probabilities edge closer to theoretical numerical values as the number of flips becomes larger.
• "Sampling Distributions.ipynb" - Creating samples for students' coffee drinking habits, calculating statistics and plotting values.