Course
Data Science
Continuing Education

Regression Analysis: Simplify Complex Data Relationships

32 Hours

Estimated learning time

Self-Paced

Progress at your own speed

Popular course

A popular course among students

About the Course

Description

This is the fifth of seven courses in the Google Advanced Data Analytics Certificate. Data professionals use regression analysis to discover the relationships between different variables in a dataset and identify key factors that affect business performance. In this course, you’ll practice modeling variable relationships. You'll learn about different methods of data modeling and how to use them to approach business problems. You’ll also explore methods such as linear regression, analysis of variance (ANOVA), and logistic regression. Google employees who currently work in the field will guide you through this course by providing hands-on activities that simulate relevant tasks, sharing examples from their day-to-day work, and helping you enhance your data analytics skills to prepare for your career. Learners who complete the seven courses in this program will have the skills needed to apply for data science and advanced data analytics jobs. This certificate assumes prior knowledge of foundational analytical principles, skills, and tools covered in the Google Data Analytics Certificate. By the end of this course, you will: -Explore the use of predictive models to describe variable relationships, with an emphasis on correlation -Determine how multiple regression builds upon simple linear regression at every step of the modeling process -Run and interpret one-way and two-way ANOVA tests -Construct different types of logistic regressions including binomial, multinomial, ordinal, and Poisson log-linear regression models

This course is part of program

You can only buy it along with program.

Sections

Schedule

Asynchronous

Delivery method

Online

Deliverables

  • Hone Important Skills

    Total Upgrade

    Such as Regression Modeling, Regression, Statistical Analysis, Predictive Modelling, Python Programming, Linearity, Linear Regression