Will Kurt: An Introduction to Probability and Statistics | PyData New York 2019
This tutorial will offer a quick overview of many of the essentials of statistics used to solve real-world problems. We'll start by looking at how to build a simple ...
PyData
Data Science in Cyber-Security and Related Statistical Challenges
Data science techniques have an important role to play in the next generation of cyber-security defenses. Inside a typical enterprise computer network, a number ...
Microsoft Research
17. Bayesian Statistics
In this lecture, Prof. Rigollet talked about Bayesian approach, Bayes rule, posterior distribution, and non-informative priors. License: Creative Commons ...
MIT OpenCourseWare
An introduction to Jeffreys priors - 1
These series of videos explain what is meant by Jeffreys priors as well as how they satisfy a particular notion of 'uninformativeness'. This concept is explained ...
Ben Lambert
An introduction to inverse transform sampling
Explains how to independently sample from a distribution using inverse transform sampling. This video is part of a lecture course which closely follows the ...
Ben Lambert
5. Logistic Regression – Generating Logistic estimates using Excel and Log Loss
In this video we cover the intuition behind log loss and demonstrate the formula in an excel spreadsheet using a sample of variables on the Charles Book Club ...
Learn Analytics
Random Effects estimators - time-invariant variables effects benefit
This video indicates one of the key benefits to Random Effects Models over Fixed Effects or First Differences estimators - the fact that it allows for estimation of ...
Ben Lambert
Lagged independent variables
This video explains what the is interpretation of lagged independent variables in an econometric model, and introduces the concept of a 'lag distribution'.
Ben Lambert
Understanding Heteroskedasticity #errorvariances #gls #wls #ols #homoscedasticity
This video explains how to understand heteroscedasticity. Coined from the Greek word hetero (which means different or unequal), and skedastic (which means ...
CrunchEconometrix
Random Effects estimators as fGLS
This video explains how Random Effects estimators can be regarded as a type of feasible Generalised Least Squares estimator. Check out ...
Ben Lambert
Simultaneous equation models - parameter identification
This video provides some insight into the issues of attempting to identify (estimate) parameters in simultaneous equation systems. Check out ...
Ben Lambert
Multiple Linear Regression in SPSS with Assumption Testing
This video demonstrates how to conduct and interpret a multiple linear regression in SPSS including testing for assumptions. The assumptions tested include: ...
Dr. Todd Grande
Mod-01 Lec-24 Model Parameter Estimation using Gauss-Newton Method
Advanced Numerical Analysis by Prof. Sachin C. Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in.
nptelhrd
Nonlinear discrete choice model estimation
This video explains how we can go about estimating nonlinear discrete choice models; summarising both the nonlinear least squares method, and maximum ...
Ben Lambert
Multinomial Logistic Regression in R | Statistical Models | Multi class classification
In this video you will learn about what is multinomial logistic regression and how to perform this in R. It is similar to Logistic Regression but with multiple values in ...
Analytics University
21. Generalized Linear Models
In this lecture, Prof. Rigollet talked about linear model, generalization, and examples of disease occurring rate, prey capture rate, Kyphosis data, etc. License: ...
MIT OpenCourseWare
Dynamic Panel Modeling with the PANEL Procedure
Bobby Gutierrez presents dynamic panel modeling using PROC Panel in SAS/ETS®. SUBSCRIBE TO THE SAS SOFTWARE YOUTUBE CHANNEL ...
SAS Software
Regression Diagnostics (FRM Part 1 2021 – Book 2 – Chapter 9)
*AnalystPrep is a GARP-Approved Exam Preparation Provider for FRM Exams* After completing this reading, you should be able to: - Explain how to test ...
AnalystPrep
Multilevel Mixed-Effects Modeling Using MATLAB
Topics covered in this webinar include: Groups, hierarchy and advantages of LME models Preparing and organizing your data to fit LME models Specifying LME ...
MATLAB
Fit a Logistic Regression Model With SAS
In this video, you learn to create a logistic regression model and interpret the results. You learn PROC LOGISTIC syntax and how to interpret p-values, parameter ...
SAS Software
Tutorial: Statistics and Data Analysis
Ethan Meyers, Hampshire College - MIT BMM Summer Course 2018 The slides and more info are available here ...
MITCBMM
An introduction to the concept of a sufficient statistic
Explains what is meant by the concept of a 'sufficient statistic', and how these summary statistics are important in likelihood-based methods. This video is part of ...
Ben Lambert
GLS - example in matrix form
This video goes through an example of the derivation of the GLS transformation in matrix form. Check out ...
Ben Lambert
15. Factor Modeling
This lecture describes factor modeling, featuring linear, macroeconomic, fundamental, and statistical factor models, and principal components analysis. License: ...
MIT OpenCourseWare
Testing the Assumptions for Spearman's Rank-Order Correlation in SPSS
This video demonstrates how to test the assumptions for Spearman's rank-order correlation (Spearman's rho) in SPSS. The assumptions for Spearman's rho ...
Dr. Todd Grande
Lec 28, Linear Regression - I
This is Lecture 28, of lecture Series on Data Analytics with Python by Prof. A. Ramesh, Department of Management Studies, IIT Roorkee.
IIT Roorkee July 2018
Heteroscedasticity: dealing with the problems caused
This video highlights the issues which heteroscedasticity causes in estimation, and summarises the ways of dealing with these issues. Check out ...
Ben Lambert
(EViews10): How to Detect Heteroskedasticity #errorvariances #graphs #plots #variances #archlm
CrunchEconometrix This video explains how to detect heteroscedasticity. Coined from the Greek word hetero (which means different or unequal), and skedastic ...
CrunchEconometrix
Panel Data Models
Fixed Effects and Random Effects Models https://sites.google.com/site/econometricsacademy/econometrics-models/panel-data-models.
econometricsacademy
Logistic Regression - Predicted Probabilities (part 1)
I demonstrate how to calculate predicted probabilities and group membership for cases in a binary (a.k.a., binomial) logistic regression analysis. I do so through ...
how2stats
Mod-03 Lec-07 Parameter Estimation
Stochastic Hydrology by Prof. P. P. Mujumdar, Department of Civil Engineering, IISc Bangalore For more details on NPTEL visit http://nptel.iitm.ac.in.
nptelhrd
Probabilistic Programming and Bayesian Modeling with PyMC3 - Christopher Fonnesbeck
Bayesian statistics offers powerful, flexible methods for data analysis that, because they are based on full probability models, confer several benefits to analysts ...
Montreal-Python
Interpreting MLR Coefficients, Interaction Term, and after Inverse Transformation 1/y
Here is the source for the data: https://www.kaggle.com/mirichoi0218/insurance In this video I discuss how to interpret the Coefficients, b, for a multiple linear ...
Michelle Lesh
Simultaneous Equation Models: Order condition for parameter identification
This video explains the conditions which are necessary in order to be able to identify parameters in a simultaneous equation model setting. Check out ...
Ben Lambert
Binary Choice - Linear Probability and Logit Models
Pat Obi
Weighted Least Squares in practice - feasible GLS - part 1
This video explains how we go about estimating Weighted Least Squares models in practice, by first of all estimating the functional form of the heteroscedasticity.
Ben Lambert
Fixed Effects and First Differences comparison - part 1
This video explains some of the differences between Fixed Effects and First Differences estimators, indicating when it is preferable to use one over the other.
Ben Lambert
Mod-03 Lec-07 Bayesian estimation of parameters of density functions, MAP estimates
Pattern Recognition by Prof. P.S. Sastry, Department of Electronics & Communication Engineering, IISc Bangalore. For more details on NPTEL visit ...
nptelhrd
Weighted Least Squares: mathematical introduction
This video provides an introduction to Weighted Least Squares, and goes into a little detail in regards to the mathematics of the transformation. Check out ...
Ben Lambert
(Factor) Analyze This: PCA or EFA - Sam Woolford
July 31, 2015 - Genetic Counseling Training Program. More: http://www.genome.gov/27558706.
National Human Genome Research Institute
GLM in R: logistic regression example
Basic interpretation of output of logistic regression covering: slope coefficient, Z- value, Null Deviance, Residual Deviance.
Phil Chan
Discrete choice models - partial effect part 2
This video explains by means of an example, what it means to find the partial effect of a given variable on the probability of a given outcome occurring in a ...
Ben Lambert
