All episodes of 迴歸分析 Regression Analysis - Chartable

迴歸分析 Regression Analysis

Episodes

(講義) Lecture 12: Introduction to logistic regression

Published 05/17/16

(講義) Lecture 13-1: Logistic regression for contingency tables

Published 05/17/16

(講義) Lecture 13-2: Goodness-of-fit for logistic regression

Published 05/17/16

(講義) Lecture 14: Logistic regression for case-control data and conditional logistic regression

Published 05/17/16

(講義) Lecture 15: Analysis of polytomous data

Published 05/17/16

(講義) Lecture 16: Poisson regression and log-linear model

Published 05/17/16

(講義) Lecture 17: Generalized linear models

Published 05/17/16

(講義) Lecture 1-1: A review of basic statistical concepts

Published 05/17/16

(講義) Lecture 8-2: Variable selection and model building

Published 05/17/16

(講義) Lecture 1-2: Measures of association with emphasis on the difference of means

Published 05/17/16

(講義) Lecture 2: Basics of linear regression analysis

Published 05/17/16

(講義) Lecture 4: Correlation

Published 05/17/16

(講義) Lecture 5-1: Analysis of variance (ANOVA) table and prediction of y

Published 05/17/16

(講義) Lecture 5-2: Basics of multiple linear regression

Published 05/17/16

(講義) Lecture 6-1: Hypothesis testing in multiple regression

Published 05/17/16

(講義) Lecture 6-2: Polynomial terms and dummy variables

Published 05/17/16

(講義) Lecture 7: Interaction and confounding

Published 05/17/16

(講義) Lecture 8-1: Regression diagnosis

Published 05/17/16

(講義) Lecture 11: Relative risk, odds ratio and significance testing for 22 tables

Published 05/17/16

Lecture 7: Interaction and confounding

Published 05/17/16

Lecture 15: Analysis of polytomous data

Published 05/17/16

Lecture 14: Logistic regression for case-control data and conditional logistic regression

Published 05/17/16

Lecture 16: Poisson regression and log-linear model

Published 05/17/16

Lecture 17: Generalized linear models

Published 05/17/16

Lecture 5-1: Analysis of variance (ANOVA) table and prediction of y

Published 05/17/16