Overview
Regression Analysis – Fundamentals & Practical Applications
Linear regression analysis is critical for understanding and defining the strength of the relationship between variables. This analysis can be used to make predictions for a variable given the value of another known variable.
This course provides an overview of linear regression. You will learn how linear regression works, how to build effective linear regression models and how to use and interpret the information these models give us. In addition to the theory, we will perform linear regression on real data using both Excel and Python. The practical cases you will work through will be similar to those you might encounter in a business setting.
Regression Analysis – Fundamentals & Practical Applications Learning Objectives
Upon completing this course, you will be able to:
- Define linear regression and its applications
- Perform simple “pen and paper” regression calculations in Excel
- Apply Excel’s RegressIt plugin to solve advanced regression calculations
- Construct linear regression models in Python using both statsmodels and sklearn modules
- Explain the implicit assumptions behind linear regression
- Interpret regression outputs such as coefficients and p-values
- Recommend various regression techniques when appropriate
Who Should Take This Course?
Regression is the critical tool used for making inferences or predictions based on the relationships between variables. Whether you’re working as a business leader or data analyst, the theory and practical toolsets taught in this course will serve you throughout your career. No background in coding with Python is required for this course.
Common career paths for students who take the BIDA™ program are Business Intelligence, Asset Management, Data Analyst, Quantitative Analyst, and other finance careers.
Regression Analysis - Fundamentals & Practical Applications
Level 4
Approx 6.5h to complete
100% online and self-paced
Get Recognized With CFI
See All Certification ProgramsWhat you'll learn
This Course is Part of the Following Programs
Why stop here? Expand your skills and show your expertise with the professional certifications, specializations, and CPE credits you’re already on your way to earning.
- Skills Learned Financial modeling and valuation, sensitivity analysis, strategy
- Career Prep Investment banking and equity research, FP&A, corporate development
- Skills Learned Data visualization, data warehousing and transformation, data modeling and analysis
- Career Prep Business intelligence analyst, data scientist, data visualization specialist
- Skills Learned Financial Technology Fundamentals, Data Science and Machine Learning, Cryptocurrencies and Blockchain
- Career Prep Data Science and Machine Learning, Data Analyst, Business Analyst, Software Developer
What our students say
Terminology and basic working of regression models is explained in a easy to follow language. Examples demonstrate underlying concepts using both MS Excel and Python.
Farooq Anwer
Statistics and Regression is important, I have to recall all the Uni subject. But with this CFI course that is really detail yet it's interesting to go through, makes me easier to understand the topics and i found it happy learning regression with the CFI mentors. Looking forwards into next course
Arvin winatha
It was kinda hard for me, but the explanations were done well
Tina Lopa
My organization uses SAS instead of Python for statistical analysis.
