INTRODUCTION TO PROBABILISTIC MODELS
Live Online Classes: Groups/1-on-1 sessions
Description
This course provides an introduction to probability for those with little or no background in statistics. Upon completion of this course, the participant will be able to apply probabilistic concepts to the calculation of random events in inferential statistics and estimate probabilistic models for sample data.
Level: introductory
Delivery: Live Online
Weeks: 4
Prerequisites: none
Certification: yes
Learning Objectives
At the end of the course, the participant is expected to have acquired the basic probabilistic fundamentals to:
-
Understand randomness and statistical event.
-
Calculate and interpret probabilities of simple events
-
Calculate and interpret probabilities of conditional events (Bayes' Rule)
-
Recognize the characteristics of a probabilistic model
-
Propose probabilistic models to estimate the probabilistic model of the data of a sample.
-
Use R to calculate probabilities of probabilistic events.
Instructor
Henry Mendoza Rivera
Henry Mendoza Rivera is the founder and president of mystatistician.com. He is the author of several online statistics courses. He was a professor in the Department of Statistics at The University of Wisconsin-Madison, Edgewood College, San Diego Community College District, and The National University of Colombia-Bogotá. He was the former director of the National Directorate of the Academic Innovation-National University of Colombia. Currently working as a professor for the MSc in Data Science from the National University-San Diego (USA). He has provided statistical consultation and training to INVIMA - Colombia National Food and Drug Surveillance Institute, Liberty Insurance-Colombia, Colombian Institute of Family Welfare (ICBF). He has been a guest in online education in statistics at Masachusset Technology Institute (MIT), as well as at different statistics Workshops, and has presented papers at international conferences.
WEEK 1
Saturday February 5, 2022
Course Content
Week 1
Probability Basics
-
Randomness and probabilistic events.
-
Calculation of probabilities of simple events.
-
Applications and use of R.
Week 3
Random variables and probabilistic models.
-
Characteristics of probabilistic models for discrete variables.
-
Characteristics of probabilistic models for continuous variables.
Week 2
Conditional events
-
Calculation of probabilities of conditional Events (Bayes rule).
-
Applications and use of R.
Week 4
Probabilistic model fits
-
Exploration of probabilistic model fits for sample data.