Statistics - Types of sampling
This video will show you the many ways that you could sample. Remember to look for those small differences such as if you are breaking things into groups first. For more videos visit http://www.mysecretmathtutor.com
From playlist Statistics
An overview of the most popular sampling methods used in statistics. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creator-spring.com/listing/sampling-in-statistics
From playlist Sampling
What is a Sampling Distribution?
Intro to sampling distributions. What is a sampling distribution? What is the mean of the sampling distribution of the mean? Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with more than 20 different techniques: https://prof-essa.creat
From playlist Probability Distributions
Statistics: Introduction (12 of 13) Sampling: Definitions and Terms
Visit http://ilectureonline.com for more math and science lectures! We will review a sampling of definitions and terms of statistics: census, sampling frame, sampling plan, judgment sample, probability samples, random samples, systematic sample, stratified sample, and cluster sample. To
From playlist STATISTICS CH 1 INTRODUCTION
This lesson introduces the different sample methods when conducting a poll or survey. Site: http://mathispower4u.com
From playlist Introduction to Statistics
Sampling (4 of 5: Introductory Examples of Stratified Random Sampling)
More resources available at www.misterwootube.com
From playlist Data Analysis
STRATIFIED, SYSTEMATIC, and CLUSTER Random Sampling (12-4)
To create a Stratified Random Sample, divide the population into smaller subgroups called strata, then use random sampling within each stratum. Strata are formed based on members’ shared (qualitative) characteristics or attributes. Stratification can be proportionate to the population size
From playlist Sampling Distributions in Statistics (WK 12 - QBA 237)
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
Lecture 17, Interpolation | MIT RES.6.007 Signals and Systems, Spring 2011
Lecture 17, Interpolation Instructor: Alan V. Oppenheim View the complete course: http://ocw.mit.edu/RES-6.007S11 License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
From playlist MIT RES.6.007 Signals and Systems, 1987
Autoregressive Diffusion Models (Machine Learning Research Paper Explained)
#machinelearning #ardm #generativemodels Diffusion models have made large advances in recent months as a new type of generative models. This paper introduces Autoregressive Diffusion Models (ARDMs), which are a mix between autoregressive generative models and diffusion models. ARDMs are t
From playlist Papers Explained
What is "Probability sampling?" A brief overview. Four different types, their advantages and disadvantages: cluster, SRS (Simple Random Sampling), Systematic and Stratified sampling. Check out my e-book, Sampling in Statistics, which covers everything you need to know to find samples with
From playlist Sampling
Introduction to Neutron Scattering (Tutorial) by Bella Lake
PROGRAM FRUSTRATED METALS AND INSULATORS (HYBRID) ORGANIZERS: Federico Becca (University of Trieste, Italy), Subhro Bhattacharjee (ICTS-TIFR, India), Yasir Iqbal (IIT Madras, India), Bella Lake (Helmholtz-Zentrum Berlin für Materialien und Energie, Germany), Yogesh Singh (IISER Mohali, In
From playlist FRUSTRATED METALS AND INSULATORS (HYBRID, 2022)
Statistics Essentials for Analytics | R Statistics | Statistics for Data Science Training | Edureka
***** Statistics for Data Science - https://www.edureka.co/data-science-r-programming-certification-course ***** This Edureka video will provide you with a detailed introduction to data and statistics involved in Data Analysis. It will also provide you with detailed knowledge of Analytics
From playlist Data Analytics with R Tutorial Videos
Overfitting - Fitting the data too well; fitting the noise. Deterministic noise versus stochastic noise. Lecture 11 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/machine-
From playlist Machine Learning Course - CS 156
Selection of the Best System using large deviations, and multi-arm Bandits by Sandeep Juneja
Large deviation theory in statistical physics: Recent advances and future challenges DATE: 14 August 2017 to 13 October 2017 VENUE: Madhava Lecture Hall, ICTS, Bengaluru Large deviation theory made its way into statistical physics as a mathematical framework for studying equilibrium syst
From playlist Large deviation theory in statistical physics: Recent advances and future challenges
OpenModelica for discrete systems
It can be very useful to build systems using graphical tools which allow us to think about the systems on a higher conceptual level and not worry about the implementation.
From playlist Modelica
GRCon21 - gr-genalyzer, a new OOT module to characterize data converter performance
Presented by Srikanth Pagadarai at GNU Radio Conference 2021 Emerging advancements in DAC/ADC technology in terms of enabling multi-channel, multi-mode, multi-band operation and supporting multi GSPS sample rates place stringent requirements on accurately characterizing the performance o
From playlist GRCon 2021
Lecture 08 - Bias-Variance Tradeoff
Bias-Variance Tradeoff - Breaking down the learning performance into competing quantities. The learning curves. Lecture 8 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunes.apple.com/us/course/ma
From playlist Machine Learning Course - CS 156
Statistics Lesson #1: Sampling
This video is for my College Algebra and Statistics students (and anyone else who may find it helpful). It includes defining and looking at examples of five sampling methods: simple random sampling, convenience sampling, systematic sampling, stratified sampling, cluster sampling. We also l
From playlist Statistics
Deep Learning Lecture 10.3 - Restricted Boltzmann Machines
Restricted Boltzmann Machines: - Architecture - Energy - Gibbs Sampling and Contrastive Divergence
From playlist Deep Learning Lecture