Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Quizes
Exercises
Publications
Startups
Units
Show all results for
Home
Lecture
Bivariate Data Analysis: Correlation and Regression
Graph Chatbot
Related lectures (54)
Linear Regression: Estimation and Inference
Explores linear regression estimation, linearity assumptions, and statistical tests in the context of model comparison.
Linear Regression: Statistical Inference and Regularization
Covers the probabilistic model for linear regression and the importance of regularization techniques.
Regression: Linear Models
Explores linear regression, least squares, residuals, and confidence intervals in regression models.
Regression Analysis: Multivariate Data Modeling
Introduces regression analysis for multivariate data modeling, covering matrix algebra, interpretation of coefficients, and test intervals.
Regression Analysis: Model Selection and Diagnostic Tools
Explores regression analysis tools, model selection, influential points, outliers, and diagnostic plots.
Linear Regression: Least Squares
Delves into linear regression, emphasizing least squares estimation, residuals, and variance.
Linear Regression: Maximum Likelihood Approach
Covers linear regression topics including confidence intervals, variance, and maximum likelihood approach.
Multilinear Regression: Least Square Fit
Explores multilinear regression, variance, correlation, optimization, ANOVA, and design procedures.
Linear Regression Testing
Explores least squares in linear regression, hypothesis testing, outliers, and model assumptions.
Regression Analysis: Interpretation and Applications
Explores multiple regression, ANOVA, interpretation of coefficients, and regression estimation.
Nonparametric Statistics: Bayesian Approach
Explores non-parametric statistics, Bayesian methods, and linear regression with a focus on kernel density estimation and posterior distribution.
NonLinear Regression
Explores non-linear regression models, likelihood estimation, model fitting, and confidence intervals.
Probabilistic Models for Linear Regression
Covers the probabilistic model for linear regression and its applications in nuclear magnetic resonance and X-ray imaging.
Real Estate Data Analysis: Descriptive Statistics
Explores real estate data analysis through descriptive statistics, correlation, regression, and forecasting methods.
Describing Data: Statistics and Hypothesis Testing
Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.
Applied Biostatistics: Bivariate Data and Regression Analysis
Log in to Mediaspace to watch this video
Covers bivariate data analysis, correlation, and regression techniques, including interpretation of coefficients and least squares geometry.
Applied Biostatistics: Bivariate Data Analysis
Log in to Mediaspace to watch this video
Explores bivariate data analysis in applied biostatistics, covering correlation, regression, model selection, and diagnostics.
Basics of Linear Regression
Log in to Mediaspace to watch this video
Covers the basics of linear regression, including OLS estimators, hypothesis testing, and confidence intervals.
Linear Regression: Basics and Applications
Log in to Mediaspace to watch this video
Covers the basics of linear regression in machine learning, exploring its applications in predicting outcomes like birth weight and analyzing relationships between variables.
Linear Regression: Beyond the Basics
Log in to Mediaspace to watch this video
Explores advanced concepts in linear regression models, including multicollinearity, hypothesis testing, and handling outliers.
Previous
Page 1 of 3
Next
