In statistics, in the theory relating to sampling from finite populations, the sampling probability (also known as inclusion probability) of an element or member of the population, is its probability of becoming part of the sample during the drawing of a single sample. For example, in simple random sampling the probability of a particular unit to be selected into the sample is where is the sample size and is the population size. Each element of the population may have a different probability of being included in the sample. The inclusion probability is also termed the "first-order inclusion probability" to distinguish it from the "second-order inclusion probability", i.e. the probability of including a pair of elements. Generally, the first-order inclusion probability of the ith element of the population is denoted by the symbol πi and the second-order inclusion probability that a pair consisting of the ith and jth element of the population that is sampled is included in a sample during the drawing of a single sample is denoted by πij. (Wikipedia).
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
Sampling Distribution of the PROPORTION: Friends of P (12-2)
The sampling distribution of the proportion is the probability distribution of all possible values of the sample proportions. It is analogous to the Distribution of Sample Means. When the sample size is large enough, the sampling distribution of the proportion can be approximated by a norm
From playlist Sampling Distributions in Statistics (WK 12 - QBA 237)
Sampling Distributions of Means
This is an old video. See StatsMrR.com for access to hundreds of 1-3 minute, well-produced videos for learning Statistics. In this older video: Understanding and working with sampling distributions of means. Calculating the mean and standard deviation and the probability associated with
From playlist Older Statistics Videos and Other Math Videos
Understanding and calculating probabilities involving the difference of sample proportions using the joint distribution of the difference of sampling distributions of proportions
From playlist Unit 7 Probability C: Sampling Distributions & Simulation
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
7D AI Further Understanding Sample Means
Further examples of sample means and how they can result from discrete distributions
From playlist Unit 7 Probability C: Sampling Distributions & Simulation
Conditions Required to Use Normal to Approximate Sample Proportions
Sample proportions, like binomial successes, are discrete. As long as large samples are taken so np and n(1-p) are both at least 10, a continuous normal distribution yields an acceptable approximation of the probabilities associated with a sample proportion distribution.
From playlist Unit 7 Probability C: Sampling Distributions & Simulation
An overview and introduction to understanding sampling distributions of proportions [sample proportions] and how to calculate them
From playlist Unit 7 Probability C: Sampling Distributions & Simulation
Overview of non probability sampling; advantages and disadvantages, types. 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
Probability and non-probability sampling
In this video, Professor Matthew Salganik discusses probability and non-probability sampling for survey research in the digital age. Link to slides: https://github.com/compsocialscience/summer-institute/blob/master/2020/materials/day4-surveys/02-nonprobability-sampling.pdf Links to other m
From playlist SICSS 2020
SICSS 2018 - Probability and Non Probability Sampling (Day 4. June 21, 2018)
Matthew Salganik talks about probability and non-probability sampling at the 2018 Summer Institute in Computational Social Science at Duke University. Slide and materials here: https://compsocialscience.github.io/summer-institute/2018/teaching-learning-materials
From playlist All Videos
Excel 2013 Statistical Analysis #25: Probability Basics: Sample Points, Events & Event Probabilities
Download Excel file: https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch04/Excel2013StatisticsChapter04.xlsm Download pdf notes file: https://people.highline.edu/mgirvin/AllClasses/210Excel2013/Ch04/Ch04PDFBusn210.pdf Topics in this video: 1. (00:12) Review Handwritten PDF Notes
From playlist Excel for Statistical Analysis in Business & Economics Free Course at YouTube (75 Videos)
Central Limit Theorem - Sampling Distribution of Sample Means - Stats & Probability
This statistics video tutorial provides a basic introduction into the central limit theorem. It explains that a sampling distribution of sample means will form the shape of a normal distribution regardless of the shape of the population distribution if a large enough sample is taken from
From playlist Statistics
Accept-Reject Sampling : Data Science Concepts
How to sample from a distribution WITHOUT the CDF or even the full PDF! Inverse Transform Sampling Video: https://www.youtube.com/watch?v=9ixzzPQWuAY
From playlist Data Science Concepts
Excel Statistical Analysis 16: Introduction to Probability. Power Query & Pivot Table Example too
Download Excel File: https://excelisfun.net/files/Ch04-ESA.xlsm pdf notes: https://excelisfun.net/files/Ch04-ESA.pdf Learn about the basics of probability: Topics: 1. (00:00) Introduction 2. (00:58) Examples of Probability 3. (02:46) What is Probability? Define Probability. 4. (05:14) Type
From playlist Excel Statistical Analysis for Business Class Playlist of Videos from excelisfun
Descriptions of Probability and Sampling Statistics Course Review (QBA 237 Block C-Weeks 9-12)
We review the highlights of the third four weeks of business statistics in which we learned about about discrete probability distributions, continuous probability distributions, Sampling, and sampling distributions. This is a review of how we use probability, various probability distribut
From playlist Basic Business Statistics (QBA 237 - Missouri State University)
Henrik Hult: Power-laws and weak convergence of the Kingman coalescent
The Kingman coalescent is a fundamental process in population genetics modelling the ancestry of a sample of individuals backwards in time. In this paper, weak convergence is proved for a sequence of Markov chains consisting of two components related to the Kingman coalescent, under a pare
From playlist Probability and Statistics
Lecture 02 - Is Learning Feasible?
Is Learning Feasible? - Can we generalize from a limited sample to the entire space? Relationship between in-sample and out-of-sample. Lecture 2 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
From playlist Courses and Series
Unit 7 Recap of Sampling Distributions and Glimpse at Inferential Statistics Next
This displays all the sampling distributions and joint sampling distributions with means, standard deviations. It also connects these to hypothesis testing and confidence intervals
From playlist Unit 7 Probability C: Sampling Distributions & Simulation