IIRF Online > Development > Data Science > Data Analysis > Probability and Statistics: To p or not to p?
Probability and Statistics: To p or not to p? by Coursera
Skills you will learn!
Curriculum
15 Topics
Welcome!
1.1 The Monty Hall Problem
1.2 Decision Making Under Uncertainty
1.3 Uncertainty in the News
1.4 Simplicity vs. Complexity - The Need for Models
1.5 Safe to Assume? Beware When Model Assumptions Go Wrong!
1.6 Roadmap of the Course
Week One Summary and Key Takeaways
1.1 The Monty Hall Problem
1.2 Decision Making Under Uncertainty
1.3 Uncertainty in the News
1.4 Simplicity vs. Complexity - The Need for Models
1.5 Safe to Assume? Beware When Model Assumptions Go Wrong!
1.6 Roadmap of the Course
Week One Quiz
14 Topics
2.1 Probability Principles
2.2 Simple Probability Distributions
2.3 Expectation of Random Variables
2.4 Bayesian Updating
2.5 Parameters
2.6 The Distribution Zoo
Week Two Summary and Key Takeaways
2.1 Probability Principles
2.2 Simple Probability Distributions
2.3 Expectation of Random Variables
2.4 Bayesian Updating
2.5 Parameters
2.6 The Distribution Zoo
Week Two Quiz
16 Topics
3.1 Classify Your Variables!
3.2 Data Visualisation
3.3 Descriptive Statistics - Measures of Central Tendency
3.4 Descriptive Statistics - Measures of Spread
3.5 The Normal Distribution
3.6 Variance of Random Variables
Week Three Summary and Key Takeaways
3.1 Classify Your Variables!
3.2 Data Visualisation
3.3 Descriptive Statistics - Measures of Central Tendency
3.4 Descriptive Statistics - Measures of Spread
3.5 The Normal Distribution
3.6 Variance of Random Variables
Week Three Quiz
Assignment One: Descriptive Statisticss
14 Topics
4.1 Introduction to Sampling
4.2 Random Sampling
4.3 Further Random Sampling
4.4 Sampling Distributions
4.5 Sampling Distribution of the Sample Mean
4.6 Confidence Intervals
Week Four Summary and Key Takeaways
4.1 Introduction to Sampling
4.2 Random Sampling
4.3 Further Random Sampling
4.4 Sampling Distributions
4.5 Sampling Distribution of the Sample Mean
4.6 Confidence Intervals
Week Four Quiz
15 Topics
5.1 Statistical Juries
5.2 Type I and Type II errors
5.3 P-values Effect Size and Sample Size Influences
5.4 Testing a Population Mean Claim
5.5 The Central Limit Theorem
5.6 Proportions: Confidence Intervals and Hypothesis Testing
Week Five Summary and Key Takeaways
5.1Statistical Juries
5.2 Type I and Type II errors
5.3 P-values Effect Size and Sample Size Influences
5.4 Testing a Population Mean Claim
5.5 The Central Limit Theorem
5.6 Proportions: Confidence Intervals and Hypothesis Testing
Week Five Quiz
Assignment Two: Hypothesis Testing
13 Topics
6.1 Decision Tree Analysis
6.2 Risk
6.3 Linear Regression
6.4 Linear Programming
6.5 Monte Carlo Simulation
6.6 Overview of the Course and Next Steps
6.1 Decision Tree Analysis
6.2 Risk
6.3 Linear regression
6.4 Linear Programming
6.5 Monte Carlo Simulation
Keep learning with the University of London
Week Six Quiz
Probability and Statistics: To p or not to p?
Related Data Analysis Courses
.webp)
Thank You!
Your review has been submitted successfully.