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Statistical Simulation in Python
Intermediate
Updated 12/2024Start course for free
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PythonProbability & Statistics4 hours16 videos58 exercises4,800 XP18,443Statement of Accomplishment
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Course Description
Get to Grips with Random Variables
Simulations are a class of computational algorithms that use random sampling to solve increasingly complex problems. Although simulations have been around for a long time, interest in this area has recently grown due to the rise in computational power and the applications across Artificial Intelligence, Physics, Computational Biology and Finance just to name a few.This course provides hands-on experience with simulations using real-world applications, starting with an introduction to random variables and the tools you need to run a simulation.
Gain an Introduction to Probability Concepts
The second chapter in this course provides an overview of probability concepts, using practice exercises based on card games and well-known probability puzzles to provide a framework for your new knowledge. You’ll finish this chapter by modeling an eCommerce advertising simulation.Discover Resampling Methods and Applications
The third chapter looks at different resampling methods, including bootstrap resampling, jackknife resampling, and permutation testing. Once you’ve completed this course, you’ll be able to add these methods to your data analysis process.Learn to Use Simulation for Business and Build Your Portfolio
Simulation has many real-world applications, especially in the world of business. The final chapter in this course looks at these, and takes you through a business planning problem to get you used to using your new skills in a business setting. You’ll look at modeling profits, optimizing costs, and getting started with power analysis.Prerequisites
Sampling in Python1
Basics of Randomness & Simulation
2
Probability & Data Generation Process
3
Resampling Methods
4
Advanced Applications of Simulation
Statistical Simulation in Python
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