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Probability and Statistics: To p or not to p?
  • Level Foundation
  • Duration 16 hours
  • Course by University of London
  • Offered by

About

We live in an uncertain and complex world, yet we continually have to make decisions in the present with uncertain future outcomes. Indeed, we should be on the look-out for "black swans" - low-probability high-impact events. To study, or not to study? To invest, or not to invest? To marry, or not to marry? While uncertainty makes decision-making difficult, it does at least make life exciting! If the entire future was known in advance, there would never be an element of surprise. Whether a good future or a bad future, it would be a known future. In this course we consider many useful tools to deal with uncertainty and help us to make informed (and hence better) decisions - essential skills for a lifetime of good decision-making. Key topics include quantifying uncertainty with probability, descriptive statistics, point and interval estimation of means and proportions, the basics of hypothesis testing, and a selection of multivariate applications of key terms and concepts seen throughout the course.

Modules

Week One

    • 8 Videos
    • 6 Readings
    • 1 Assignment
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1 Assignment

  • Week One Quiz

8 Videos

  • 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

6 Readings

  • 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 Two

    • 7 Videos
    • 6 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week Two Quiz

7 Videos

  • 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

6 Readings

  • 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 Three

    • 7 Videos
    • 6 Readings
    • 1 PeerReview
    • 1 Assignment
Show info about module content

1 Assignment

  • Week Three Quiz

1 Peer Review

  • Assignment One: Descriptive Statistics

7 Videos

  • 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

6 Readings

  • 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 Four

    • 7 Videos
    • 6 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week Four Quiz

7 Videos

  • 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

6 Readings

  • 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 Five

    • 7 Videos
    • 6 Readings
    • 1 PeerReview
    • 1 Assignment
Show info about module content

1 Assignment

  • Week Five Quiz

1 Peer Review

  • Assignment Two: Hypothesis Testing

7 Videos

  • 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

6 Readings

  • 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 Six

    • 6 Videos
    • 6 Readings
    • 1 Assignment
Show info about module content

1 Assignment

  • Week Six Quiz

6 Videos

  • 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 Readings

  • 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

Auto Summary

Embark on a journey through the world of uncertainty with the "Probability and Statistics: To p or not to p?" course, offered by Coursera. This foundational course delves into the essential tools and techniques of probability and statistics to equip you with the skills needed for informed decision-making in an unpredictable world. Guided by expert instructors, you will explore the quantification of uncertainty, delve into descriptive statistics, and master the principles of hypothesis testing. The course also covers point and interval estimation for means and proportions, and introduces multivariate applications of key statistical concepts. Spanning 960 minutes of comprehensive content, this course is ideal for beginners seeking to build a solid foundation in maths and statistics. With a starter subscription option available, you can access valuable knowledge and practical insights tailored for anyone aiming to enhance their decision-making capabilities in both personal and professional contexts. Join us to transform how you approach uncertainty and make better decisions with confidence.

Dr James Abdey
Instructor

Dr James Abdey