Completion

CERTIFICATE

Regression Modeling in Practice

Name: Regression Modeling in Practice
Rating: 4.4 (273 reviews)

Become proficient in linear, multiple, and logistic regression analysis using SAS or Python to derive valuable insights from data.

Course Cost

Free course

Intermediate

Skill Level

9 Hours

Self-paced lessons

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Analysis and Interpretation Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

4.4

34,819 Enrolled

Jen Rose

Lisa Dierker

English

4.4

34,819 Enrolled

English

Jen Rose

Lisa Dierker

What you'll learn

Apply linear regression for quantitative response variables

Implement multiple regression with multiple predictors

Perform logistic regression for binary outcomes

Evaluate model fit using diagnostic techniques

Handle confounding variables and polynomial regression

Skills you'll gain

Regression Analysis

Linear Regression

Multiple Regression

Logistic Regression

Statistical Modeling

Data Analysis

Python Programming

SAS Programming

Model Evaluation

Statistical Inference

This course includes:

3.05 Hours PreRecorded video

1 peer review per module

Access on Mobile, Tablet, Desktop

FullTime access

Shareable certificate

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PROVIDED BY

Top companies offer this course to their employees

Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.

There are 4 modules in this course

This comprehensive course focuses on regression analysis as a powerful tool for data analysis. Students learn various regression techniques, from basic linear regression to multiple regression and logistic regression. The curriculum covers model assumptions, interpretation of coefficients, regression diagnostics, and handling of confounding variables. Through hands-on practice with either SAS or Python, learners develop practical skills in building and evaluating regression models for different types of data and research questions.

Introduction to Regression

Module 1 · 2 Hours to complete

This session starts where the Data Analysis Tools course left off. This first set of videos provides you with some conceptual background about the major types of data you may work with, which will increase your competence in choosing the statistical analysis that's most appropriate given the structure of your data.

Skills you'll gain

Data Analysis

Regression Analysis

Research Methods

Statistical Analysis

This course includes:

4 Videos

5 Reading Materials

Basics of Linear Regression

Module 2 · 3 Hours to complete

In this session, we discuss more about the importance of testing for confounding, and provide examples of situations in which a confounding variable can explain the association between an explanatory and response variable. You will test and interpret associations using basic linear regression analysis for a quantitative response variable.

Skills you'll gain

Linear Regression

Statistical Analysis

Confounding Variables

Quantitative Analysis

This course includes:

8 Videos

9 Reading Materials

Multiple Regression

Module 3 · 2 Hours to complete

Multiple regression analysis is tool that allows you to expand on your research question, and conduct a more rigorous test of the association between your explanatory and response variable by adding additional quantitative and/or categorical explanatory variables to your linear regression model.

Skills you'll gain

Multiple Regression

Statistical Analysis

Model Evaluation

Confidence Intervals

This course includes:

10 Videos

2 Reading Materials

Logistic Regression

Module 4 · 2 Hours to complete

Fee Structure

Reviews

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Faculties

These are the expert instructors who will be teaching you throughout the course. With a wealth of knowledge and real-world experience, they're here to guide, inspire, and support you every step of the way. Get to know the people who will help you reach your learning goals and make the most of your journey.

4.8

Reviews

92,317

Students

Courses

Jen Rose

Jennifer Rose serves as Director of the Center for Pedagogical Innovation and Professor of the Practice at Wesleyan University's Quantitative Analysis Center. Along with colleague Lisa Dierker, she co-developed the "Passion-Driven Statistics" curriculum, which has transformed statistics education through project-based learning approaches. Her innovative teaching methods have earned multiple National Science Foundation grants to disseminate their educational model nationwide. As Director of the Institutional Review Board and Professor of the Practice in the Center for Pedagogical Innovation, she has significantly influenced how statistics is taught to undergraduate students. Her course "Intro to Statistical Consulting" provides students with real-world experience by connecting them with nonprofits for data analysis projects. Her work has extended the reach of this innovative teaching approach to thousands of students globally through online platforms and institutional partnerships.

4.8

Reviews

92,317

Students

Courses

Lisa Dierker

Lisa Dierker, Professor of Psychology at Wesleyan University, has transformed statistical education through her innovative "Passion Driven Statistics" curriculum. Her expertise spans chronic disease epidemiology and advanced statistical methods, leading to significant National Science Foundation funding for developing accessible, project-based teaching approaches. Her collaborative work across disciplines including public health, medicine, engineering, and neuroscience has produced groundbreaking research while making statistics more engaging for diverse student populations. Through her leadership in curriculum development and cross-disciplinary research, she has significantly influenced how quantitative methods are taught at the undergraduate level, while maintaining active research in epidemiology and public health.

Intermediate

Skill Level

9 Hours

Self-paced lessons

Course Cost

Free course

Completion

CERTIFICATE

Frequently asked Questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.

Regression Modeling in Practice

What you'll learn

Skills you'll gain

This course includes:

Get a Completion Certificate

Get a Completion Certificate

Top companies offer this course to their employees

There are 4 modules in this course

Introduction to Regression

Skills you'll gain

This course includes:

Basics of Linear Regression

Skills you'll gain

This course includes:

Multiple Regression

Skills you'll gain

This course includes:

Logistic Regression

Skills you'll gain

This course includes:

Fee Structure

Reviews

Faculties

Frequently asked Questions

When will I have access to the lectures and assignments?

What will I get if I subscribe to this Specialization?

What is the refund policy?

Is financial aid available?