Probability and Statistics: Complete Course 2024
Probability and Statistics: Complete Course 2024
Learn the Probability and Statistics You Need to Succeed in Data Science and Business Analytics
Created by Woody Lewenstein | 16.5 hours on-demand video course
This is Probability and Statistics: Complete Course 2024 designed to take you from beginner to expert in probability and statistics. It is designed to be practical, hands on and suitable for anyone who wants to use statistics in data science, business analytics or any other field to make better informed decisions. Videos packed with worked examples and explanations so you never get lost, and every technique covered is implemented in Microsoft Excel so that you can put it to use immediately.
Key concepts taught in the course are:
- Descriptive Statistics: Averages, measures of spread, correlation and much more.
- Cleaning Data: Identifying and removing outliers
- Visualization of Data: All standard techniques for visualizing data, embedded in Excel.
- Probability: Independent Events, conditional probability and Bayesian statistics.
- Discrete Distributions: Binomial, Poisson, expectation and variance and approximations.
- Continuous Distributions: The Normal distribution, the central limit theorem and continuous random variables.
- Hypothesis Tests: Using binomial, Poisson and normal distributions, T-tests and confidence intervals.
- Regression: Linear regression analysis, correlation, testing for correlation, non-linear regression models.
- Quality of Tests: Type I and Type II errors, power and size, p-hacking.
- Chi-Squared Tests: The chi-squared distribution and how to use it to test for association and goodness of fit.
- Much, much more!
It requires no prior knowledge, with the exception of 2 optional videos at the end of the continuous distribution chapter, in which knowledge of calculus is required).
Probability and Statistics: Complete Course
What you’ll learn
- Descriptive Statistics: Averages, measures of spread, correlation and much more.
- Cleaning Data: Identifying and removing outliers
- Visualization of Data: All standard techniques for visualizing data, embedded in Excel.
- Probability: Independent Events, conditional probability and Bayesian statistics.
- Discrete Distributions: Binomial, Poisson, expectation and variance and approximations.
- Continuous Distributions: The Normal distribution, the central limit theorem and continuous random variables.
- Hypothesis Tests: Using binomial, Poisson and normal distributions, T-tests and confidence intervals.
- Regression: Linear regression analysis, correlation, testing for correlation, non-linear regression models.
- Quality of Tests: Type I and Type II errors, power and size, p-hacking.
- Chi-Squared Tests: The chi-squared distribution and how to use it to test for association and goodness of fit.
- Much, much more!
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Who this course is for:
- Data Scientists
- Business Analysts
- Business Students
- People studying Statistics
- Anyone looking to power their decision making with a thorough understanding of statistics.
