In science, randomized experiments are the experiments that allow the greatest reliability and validity of statistical estimates of treatment effects. Randomization-based inference is especially important in experimental design and in survey sampling. (Wikipedia).
Statistics Lesson #3: Randomized Experiments & Observational Studies
This video is for my College Algebra and Statistics students (and anyone else who may find it helpful). I define a randomized experiment, show a couple of examples, and define some important vocabulary related to experiments. Then I define an observational study, give an example, and discu
From playlist Statistics
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Random and systematic error explained: from fizzics.org
In scientific experiments and measurement it is almost never possible to be absolutely accurate. We tend to make two types of error, these are either random or systematic. The video uses examples to explain the difference and the first steps you might take to reduce them. Notes to support
From playlist Units of measurement
Misunderstanding of Randomized Controlled Trials #shorts
#causalinference #machinelearning #datascience #rct #abtest #shorts REFERENCES [1] Understanding & Misunderstanding Randomized Controlled Trials: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6019115/
From playlist Causal Inference
Random Sampling - Statistical Inference
In this video I talk about Random Sampling - I give you a full, in-depth primer about random sampling and what sampling is in general. I then discuss the two ways of taking a random sample from a population (1st way: No replacement; 2nd way: With replacement) and point out the difference b
From playlist Statistical Inference
Statistics: Ch 5 Discrete Random Variable (1 of 27) What is a Random Variable?
Visit http://ilectureonline.com for more math and science lectures! To donate: http://www.ilectureonline.com/donate https://www.patreon.com/user?u=3236071 We will learn a random variable is a variable which represents the outcome of a trial, an experiment, or an event. It is a specific n
From playlist STATISTICS CH 5 DISCRETE RANDOM VARIABLE
Prob & Stats - Random Variable & Prob Distribution (2 of 53) Random Variable - Terminology Review
Visit http://ilectureonline.com for more math and science lectures! In this video I will define and reviews terminologies associated with random variables. Next video in series: http://youtu.be/ebP7x2zviBI
From playlist iLecturesOnline: Probability & Stats 2: Random Variable & Probability Distribution
The Most Powerful Tool Based Entirely On Randomness
We see the effects of randomness all around us on a day to day basis. In this video we’ll be discussing a couple of different techniques that scientists use to understand randomness, as well as how we can harness its power. Basically, we'll study the mathematics of randomness. The branch
From playlist Classical Physics by Parth G
L05.2 Definition of Random Variables
MIT RES.6-012 Introduction to Probability, Spring 2018 View the complete course: https://ocw.mit.edu/RES-6-012S18 Instructor: John Tsitsiklis License: Creative Commons BY-NC-SA More information at https://ocw.mit.edu/terms More courses at https://ocw.mit.edu
From playlist MIT RES.6-012 Introduction to Probability, Spring 2018
Ses 2 | MIT Abdul Latif Jameel Poverty Action Lab Executive Training
Session 2: Why randomize? Speaker: Dan Levy See the complete course at: http://ocw.mit.edu/jpal License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT Abdul Latif Jameel Poverty Action Lab Executive Training
Discrete & Continuous random variables
Let's talk about discrete and continuous random variables. For more information, check out the blog post on probability fundamentals in Machine Learning: https://towardsdatascience.com/probability-for-machine-learning-b4150953df09 BLOG: https://medium.com/@dataemporium Maximum Likeliho
From playlist The Math You Should Know
Comparison of systematic and random error. Types of systematic error, including offset error and scale factor error/
From playlist Experimental Design
Scientific vs. STATISTICAL Experiments: Getting an Outcome (9-1)
In a science experiment, we measure stuff; in a statistical experiment, we compute probability. Scientific experiments yield replicable outcomes; statistical experiments yield random outcomes. Random means that we cannot reliably predict the outcome. A Random Variable is any outcome of a
From playlist Discrete Probability Distributions in Statistics (WK 9 - QBA 237)
5. Discrete Random Variables I
MIT 6.041 Probabilistic Systems Analysis and Applied Probability, Fall 2010 View the complete course: http://ocw.mit.edu/6-041F10 Instructor: John Tsitsiklis Chapters 0:00 Intro 0:54 Outline 2:36 Random Variable 24:53 Expectation 43:00 Variance License: Creative Commons BY-NC-SA More inf
From playlist MIT 6.041SC Probabilistic Systems Analysis and Applied Probability, Fall 2013
For more information, check out the blog post on probability fundamentals in Machine Learning: https://towardsdatascience.com/probability-for-machine-learning-b4150953df09 BLOG: https://medium.com/@dataemporium ⭐ Coursera Plus: $100 off until September 29th, 2022 for access to 7000+ cour
From playlist The Math You Should Know
Probability Mass Functions - EXPLAINED!
Let's talk about probability mass functions and how they are used in machine learning! For more information, check out the blog post on probability fundamentals in Machine Learning: https://towardsdatascience.com/probability-for-machine-learning-b4150953df09 BLOG: https://medium.com/@dat
From playlist The Math You Should Know
What, why, and which experiments?
Professor Matt Salganik of Princeton University discusses how to think about experiments in the age of computational social science. Link to slides discussed in this video: https://github.com/compsocialscience/summer-institute/blob/master/2020/materials/day6-experiments/01-what-why-which-e
From playlist SICSS 2020
Probability Distribution Functions - EXPLAINED!
Probability distribution functions are functions that map an event to the probability of occurrence of that event. Let's talk about them. For more information, check out the blog post on probability fundamentals in Machine Learning: https://towardsdatascience.com/probability-for-machine-l
From playlist The Math You Should Know
Probability and Information Theory
Cryptography and Network Security by Prof. D. Mukhopadhyay, Department of Computer Science and Engineering, IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
From playlist Computer - Cryptography and Network Security