Scientific experiments often consist of comparing two or more sets of data. This data is described as unpaired or independent when the sets of data arise from separate individuals or paired when it arises from the same individual at different points in time. For example one clinical trial might involve measuring the blood pressure from one group of patients who were given a medicine and the blood pressure from another group not given it. This would be unpaired data. Another clinical trial might record the blood pressure in the same group of patients before and after giving the medicine. In this case the data is "paired" as it is likely the blood pressure after giving the medicine will be related to the blood pressure of that patient before the medicine was given. The statistical tests used to compare sets of data have been designed for data that is either paired or unpaired and it is important to use the correct test to prevent erroneous results. Examples of tests for unpaired data: * Pearson's Chi-squared test * Fisher's Exact Test Examples of tests suitable for paired data: * McNemar's Test (Wikipedia).
A Gentle Introduction to Paired Samples t Test (11-6)
The paired samples t test uses repeated measures in which the same subjects are used in all treatment conditions. This is typical of a “before and after” design. Another way to use a paired samples t test is with matched pairs. It tests whether the average difference between two measureme
From playlist WK11 Independent Sample t Tests and Paired t Tests - Online Statistics for the Flipped Classroom
2 Sample t Test v Paired t Test
Identifying the difference between situations when a 2-sample t Test is appropriate and when a paired t Test is appropriate, including the recognition of paired dependent data versus independent samples.
From playlist Unit 9: t Inference and 2-Sample Inference
Mean of Grouped Frequency Tables
"Calculate mean from grouped frequency tables."
From playlist Data Handling: Frequency Tables
06 Paired Samples t-Tests in SPSS – SPSS for Beginners
2021 NEW SERIES for SPSS 27: https://youtu.be/PN-H8GikRQ0 You use a paired samples t test in two research designs. One, you conduct a study with a before-and-after design, in which you measure the same sample at two different times with a treatment in between. Two, you have paired particip
From playlist Introduction to SPSS Statistics 27
Hypothesis Test with Paired Sample Data in StatCrunch
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Hypothesis Test with Paired Sample Data in StatCrunch
From playlist Statistics
Powered by https://www.numerise.com/ Types of data (2)
From playlist Collecting data
Matched or Paired Samples T-Test - Hypothesis Testing
This Statistics video tutorial provides a basic introduction into matched or paired samples. It explains how to use the T-test and the student's t-distribution to determine whether or not if you should reject the null hypothesis in favor of the alternative hypothesis. It also explains ho
From playlist Statistics
Full Hypothesis Test for Paired Data using StatCrunch
Please Subscribe here, thank you!!! https://goo.gl/JQ8Nys Full Hypothesis Test for Paired Data using StatCrunch
From playlist Statistics
Combining Data From Multiple Cells In Excel | How To Combine Data In Excel | Simplilearn
This video is based on Combining Data From Multiple Cells In Excel. Combining data in excel comes handy when you want to create a considered profile type cell that includes all the major information at one place. For example, employee name, ID and mailing address. This tutorial will guide
From playlist Microsoft Excel Tutorial Videos 🔥[2022 Updated]
AugSBERT: Domain Transfer for Sentence Transformers
🎁 Free NLP for Semantic Search Course: https://www.pinecone.io/learn/nlp When building language models, we can spend months optimizing training and model parameters, but it's useless if we don't have the correct data. The success of our language models relies first and foremost on data.
From playlist NLP for Semantic Search Course
ParamHypTestP2.7.Paired t-test
This video is brought to you by the Quantitative Analysis Institute at Wellesley College. The material is best viewed as part of the online resources that organize the content and include questions for checking understanding: https://www.wellesley.edu/qai/onlineresources
From playlist Parametric Hypothesis Tests, Part 2
Making The Most of Data: Augmented SBERT
🎁 Free NLP for Semantic Search Course: https://www.pinecone.io/learn/nlp ML models are data-hungry. They consume massive amounts of data to identify generalized patterns and apply those learned patterns to new data. As models get bigger, so do datasets. And although we have seen an explo
From playlist NLP for Semantic Search Course
Clustering (2): Hierarchical Agglomerative Clustering
Hierarchical agglomerative clustering, or linkage clustering. Procedure, complexity analysis, and cluster dissimilarity measures including single linkage, complete linkage, and others.
From playlist cs273a
RT/DSC - Eric Wernert talks about scalable and distributed visualization using Paraview
Eric Wernert gives a talk about scalable and distributed visualization using Paraview at the Big Data for Science workshop held at the Pervasive Technology Institute, Indiana University. This event was put on by PTI's Digital Science Center July 26th - July 30th, 2010. For more informat
From playlist Digital Science Center (DSC)
How to do a Paired Samples t Test in SPSS (11-7)
Using a dog training example, we compare two types of reinforcement training using a Paired Samples t-test. We work through the five steps of hypothesis testing, and conduct the Paired Samples t-test in SPSS. We compute Cohen’s d, we interpret the results, and write them up in proper APA
From playlist WK11 Independent Sample t Tests and Paired t Tests - Online Statistics for the Flipped Classroom
HEDS | Wide Ranging Ionic Transport Coefficients for High-Energy Density Applications
HEDS Seminar Series – Luke Stanek – May 27th, 2021 LLNL-VIDEO- 825018
From playlist High Energy Density Science Seminar Series
Train Sentence Transformers by Generating Queries (GenQ)
🎁 Free NLP for Semantic Search Course: https://www.pinecone.io/learn/nlp Fine-tuning effective dense retrieval models is challenging. Bi-encoders (sentence transformers) are the current best models for dense retrieval in semantic search. Unfortunately, they're also notoriously data-hungry
From playlist Recommended
Grouped frequency tables (continuous)
Powered by https://www.numerise.com/ Grouped frequency tables (continuous)
From playlist Collecting data
Introduction to Dense Text Representation - Part 3
In the third part, I present advanced applications and training methods to learn dense text representations. Topics included: - Multilingual Text Embeddings - Data Augmentation - Unsupervised Text Embedding learning - Neural Search Slides: https://nils-reimers.de/talks/2021-06-Intro_Dens
From playlist Introduction to Dense Text Representation