Variance reduction | Sampling (statistics) | Sampling techniques
In statistics, stratified sampling is a method of sampling from a population which can be partitioned into subpopulations. In statistical surveys, when subpopulations within an overall population vary, it could be advantageous to sample each subpopulation (stratum) independently. Stratification is the process of dividing members of the population into homogeneous subgroups before sampling. The strata should define a partition of the population. That is, it should be collectively exhaustive and mutually exclusive: every element in the population must be assigned to one and only one stratum. Then simple random sampling is applied within each stratum. The objective is to improve the precision of the sample by reducing sampling error. It can produce a weighted mean that has less variability than the arithmetic mean of a simple random sample of the population. In computational statistics, stratified sampling is a method of variance reduction when Monte Carlo methods are used to estimate population statistics from a known population. (Wikipedia).
What is cluster sampling? Comparison to stratified sampling. Advantages and disadvantages. 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
From playlist Sampling
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)
Introduction to Stratified, Cluster, Systematic, and Convenience Sampling
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From playlist Statistics
Stratified random sampling (1)
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Stratified random sampling (2)
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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
Sampling (4 of 5: Introductory Examples of Stratified Random Sampling)
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From playlist Data Analysis
Research Methods 1: Sampling Techniques
In this video, I discuss several types of sampling: random sampling, stratified random sampling, cluster sampling, systematic sampling, and convenience sampling. The figures presented are adopted/adapted from: https://www.pngkey.com/detail/u2y3q8q8e6o0u2t4_population-and-sample-graphic-de
From playlist Research Methods
Sampling: Stratified Sampling (Grade 5) - OnMaths GCSE Maths Revision
Topic: Sampling: Stratified Sampling Do this paper online for free: https://www.onmaths.com/sampling/ Grade: 5 This question appears on calculator higher and foundation GCSE papers. Practise and revise with OnMaths. Go to onmaths.com for more resources, like predicted GCSE Maths Papers, T
From playlist Sampling
I continue to introduce sampling techniques. In this video I go over Stratified Random Samples, Stratified Random Sample, Cluster Samples, and Multistage Samples. Check out http://www.ProfRobBob.com, there you will find my lessons organized by class/subject and then by topics within each
From playlist AP Statistics
Statistical Rethinking 2023 - 06 - Good & Bad Controls
Course details: https://github.com/rmcelreath/stat_rethinking_2023 Intro music: https://www.youtube.com/watch?v=PDohhCaNf98 Outline 00:00 Introduction 01:43 Causal implications 14:28 do-calculus 16:59 Backdoor criterion 40:48 Pause 41:22 Good and bad controls 1:09:34 Summary 1:26:27 Bonu
From playlist Statistical Rethinking 2023
GCSE Revision Video 31 - Stratified Sampling
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From playlist GCSE Quick Revision List
Statistical Rethinking 2022 Lecture 05 - Elemental Confounds
Slides and other course materials: https://github.com/rmcelreath/stat_rethinking_2022 Music: Intro: https://www.youtube.com/watch?v=bct8stbZafI Pause: https://www.youtube.com/watch?v=zT50dvlYUBQ Chapters: 00:00 Introduction 04:15 Elemental Confounds 05:45 The Fork 30:48 The Pipe 40:18 In
From playlist Statistical Rethinking 2022
Sampling Techniques & Cautions (Full Length)
I define and discuss the differences of observational studies and experiments. I then discuss the difference between a sample and a census. I introduce two types of sampling techniques that yield biased results...Voluntary Response and Convenience Sampling. I discuss Stratified Random S
From playlist AP Statistics
Statistical Rethinking 2023 - 05 - Elemental Confounds
Course details: https://github.com/rmcelreath/stat_rethinking_2023 Intro drone footage: https://www.youtube.com/watch?v=a4CKOjGPzRs Intro music: https://www.youtube.com/watch?v=USIwUgM_yuQ Outline 00:00 Introduction 04:35 The Fork 26:50 Simulating interventions 31:40 Pause 32:12 The Pipe
From playlist Statistical Rethinking 2023
Statistics Lecture 1.5 Part 2: Sampling Techniques
From playlist Statistics Playlist 1
Identify which Type of Sampling is Used MyMathlab Homework
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From playlist Statistics
Stratified random sampling (3)
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