Statistics, Probability & EDA for Data Science using Python

Learn everything from Probability & Statistics, then test your knowledge with 600+ practice questions

Created by: Krista King
Your geeky, trusty math tutor

What Will I Learn?

• Visualizing data, including bar graphs, pie charts, venn diagrams, histograms, and dot plots
• Analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots
• Data distributions, including mean, variance, and standard deviation, and normal distributions and z-scores
• Probability, including union vs. intersection and independent and dependent events and Bayes' theorem
• Discrete random variables, including binomial, Bernoulli, Poisson, and geometric random variables
• Sampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervals
• Hypothesis testing, including inferential statistics, significance level, type I and II errors, test statistics, and p-values
• Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-square

Requirements

• You should be comfortable with arithmetic (addition, subtraction, multiplication, division) of whole numbers.
• You should be comfortable with basic algebraic operations and simple equation solving.
• You'll only need simple arithmetic and algebra to solve these probability and statistics problems, so if you have that simple foundation, you'll be well prepared for this course.

Target audience

• Current probability and statistics students, or students about to start probability and statistics who are looking to get ahead
• Homeschool parents looking for extra support with probability and statistics
• Anyone who wants to study math for fun after being away from school for a while