Data transformation (statistics)

What Is Data Science?

Data science describes the activities related to collecting, storing and creating value from data. Creating value from data means using it to do useful things, like making better decisions. By analyzing data we can detect patterns in it and understand the process that generated it. This i

From playlist Data Science Dictionary

Data Transformation | Introduction to Data Mining part 16

In this Data Mining Fundamentals tutorial, we discuss the transformation of data in data preprocessing, such as attribute transformation. Attribute transformation is a function that maps the entire set of values of a given attribute to a new set of replacement values such that each old val

From playlist Introduction to Data Mining

Linear Transformations on Random Variables

I recently uploaded 200 videos that are much more concise with excellent graphics. Click the link in the upper right-hand corner of this video. It will take you to my youtube channel where videos are arranged in playlists. In this older video: Discrete and continuous variables including

From playlist Older Statistics Videos and Other Math Videos

Statistics (video 1) - Statistics of Datasets

Recordings of the corresponding course on Coursera. If you are interested in exercises and/or a certificate, have a look here: https://www.coursera.org/learn/pca-machine-learning

From playlist Statistics of Datasets

Data transformation using the Wolfram Language

In this short video I show you how to transform data for use in parametric tests. When data does not meet the assumption of normality, we can transform it using non-linear functions. I state, though, that it is probably better to use distribution-independent (non-parametric) tests. In t

From playlist Statistics

Inverse Transform Sampling : Data Science Concepts

Let's take a look at how to transform one distribution into another in data science! Note: I should have included a lambda in front of the exponential PDF. I mistakenly forgot it. I appreciate the comments which helped me realize this mistake. --- Like, Subscribe, and Hit that Bell to g

From playlist Data Science Concepts

Statistics - The vocabulary of statistics

This video will give show you a few terms that are used in statistics such as data, population, sample, parameter, statistic, and variable. Remember that it matters if you are talking about the whole group, or a portion of that group. For more videos please visit http://www.mysecretmatht

From playlist Statistics

Mean, Median, and Mode

This video explains how to determine mean, median and mode. It also provided examples. http://mathispower4u.yolasite.com/

From playlist Statistics: Describing Data

Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

https://www.patreon.com/ProfessorLeonard Statistics Lecture 3.3: Finding the Standard Deviation of a Data Set

From playlist Statistics (Full Length Videos)

Data Transformation Workflows with Anton Antonov, Session #1

In this first lecture, Anton introduces the target data transformation workflows and related concepts. Access the notebook for this lecture here: https://wolfr.am/DataTransformationsWorkflows1 You can interact directly with Anton through the Wolfram Community: https://wolfr.am/CommunityDa

From playlist Data Transformation Workflows with Anton Antonov

Signal nonstationarities and their effects on the power spectrum

This video lesson is part of a complete course on neuroscience time series analyses. The full course includes - over 47 hours of video instruction - lots and lots of MATLAB exercises and problem sets - access to a dedicated Q&A forum. You can find out more here: https://www.udemy.

From playlist NEW ANTS #2) Static spectral analysis

Standard Deviation and Linear Transformations

An introdution to Standard Deviation, it's properties, and the linear transformation process. LINEAR TRANSFORMATION AT 9:01 Check out http://www.ProfRobBob.com, there you will find my lessons organized by class/subject and then by topics within each class. Find free review test, useful

From playlist AP Statistics

Suhasini Subba Rao: Fourier based methods for spatial data observed on irregularly spaced locations

Abstract : In this talk we introduce a class of statistics for spatial data that is observed on an irregular set of locations. Our aim is to obtain a unified framework for inference and the statistics we consider include both parametric and nonparametric estimators of the spatial covarianc

From playlist Probability and Statistics

Neuroscience source separation 1a: Spectral separation

This is part one of a three-part lecture series I taught in a masters-level neuroscience course in fall of 2020 at the Donders Institute (the Netherlands). The lectures were all online in order to minimize the spread of the coronavirus. That's good for you, because now you can watch the en

From playlist Neuroscience source separation (3-part lecture series)

Why neural networks aren't neural networks

There is a better way to understand how AIs sort data, process images, and make decisions! Made for the 2021 Summer of Math Exposition: https://www.3blue1brown.com/blog/some1 Source code available here: https://gitlab.com/samsartor/nn_vis The background music is an excerpt of the endles

From playlist Summer of Math Exposition Youtube Videos

Data Science - Part IV - Regression Analysis and ANOVA Concepts

For downloadable versions of these lectures, please go to the following link: http://www.slideshare.net/DerekKane/presentations https://github.com/DerekKane/YouTube-Tutorials This lecture provides an overview of linear regression analysis, interaction terms, ANOVA, optimization, log-leve

From playlist Data Science

Geostatistics session 5 conditional simulation

Introduction to conditional simulation with Gaussian processes

From playlist Geostatistics GS240

Visu Makam: "Maximum Likelihood Estimation for Tensor Normal Models"

Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021 Workshop IV: Efficient Tensor Representations for Learning and Computational Complexity "Maximum Likelihood Estimation for Tensor Normal Models" Visu Makam - Institute for Advanced Study Abstract: We study sa

From playlist Tensor Methods and Emerging Applications to the Physical and Data Sciences 2021

Broad overview of EEG data analysis analysis

This lecture is a very broad introduction to the most commonly used data analyses in cognitive electrophysiology. There is no math, no Matlab, and no data to download. For more information about MATLAB programming: https://www.udemy.com/matlab-programming-mxc/?couponCode=MXC-MATLAB10 For

From playlist OLD ANTS #1) Introductions

Statistics (video 5): Linear Transformations, Part 1/2

Recordings of the corresponding course on Coursera. If you are interested in exercises and/or a certificate, have a look here: https://www.coursera.org/learn/pca-machine-learning

From playlist Statistics of Datasets