Statistical Modeling

 

 


 

Customize your search:

E.g., 2017-08-21
E.g., 2017-08-21
E.g., 2017-08-21
Aug 21st 2017

An introduction to commonly used linear regression models along with detailed implementation of the models within real data examples using the R statistical software. Regression Analysis is the most common statistical modeling approach used in data analysis and it is the basis for more advanced statistical and machine learning modeling.

Average: 2 (1 vote)
Self-Paced

A focus on the techniques commonly used to perform statistical inference on high throughput data. In this course you’ll learn various statistics topics including multiple testing problem, error rates, error rate controlling procedures, false discovery rates, q-values and exploratory data analysis. We then introduce statistical modeling and how it is applied to high-throughput data. In particular, we will discuss parametric distributions, including binomial, exponential, and gamma, and describe maximum likelihood estimation.

No votes yet
Feb 20th 2017

Learn the technology of modelling, as used in computational face recognition or in surgeries, with this free online course. Statistical shape models are one of the most important technologies in computer vision and medical image analysis. With this technology, the computer learns the characteristic shape variations of an object or organ. The model resulting from this analysis may then be used in implant design, image analysis, surgery planning and many other fields.

Average: 10 (1 vote)

Feb 15th 2017

A comprehensive course on conducting and presenting policy evaluations using interrupted time series analysis. Interrupted time series analysis and regression discontinuity designs are two of the most rigorous ways to evaluate policies with routinely collected data. ITSx comprehensively introduces analysts to interrupted time series analysis (ITS) and regression discontinuity designs (RD) from start to finish, including definition of an appropriate research question, selection and setup of data sources, statistical analysis, interpretation and presentation, and identification of potential pitfalls.

No votes yet
Dec 1st 2016

Learn how to conduct risk analysis of different projects using both conceptual and practical developments in modern finance. This finance course will begin by exposing learners to the critical role risk plays in evaluating projects.

Average: 4.4 (5 votes)
Aug 15th 2016

This course provides theoretical and practical training on the increasingly popular logistic regression model, which has become the standard analytical method for use with a binary response variable. This is a hands-on, applied course where students will become proficient at using computer software to analyze data drawn primarily from the fields of medicine, epidemiology, and public health.

No votes yet

Feb 15th 2016

Regression modeling is the standard method for analysis of continuous response data. This course provides theoretical and practical training in statistical modeling with particular emphasis on linear and multiple regression.

Average: 10 (1 vote)
Dec 15th 2015

A focus on the techniques commonly used to perform statistical inference on high throughput data.

Average: 6.5 (2 votes)