Summary
Models the relationship between variables, predicting a response from one or more predictors.
In depth
Linear regression fits y = a + bx by least squares; R² shows variance explained. Multiple regression includes several predictors; logistic regression predicts binary outcomes. Check residuals.
Check linearity, residuals, outliers. R² can be inflated by adding variables; use adjusted R². Extrapolation beyond data is risky.
Remember: regression finds associations unless the design supports causality.
Frequently asked questions
What is Regression Analysis?
Models the relationship between variables, predicting a response from one or more predictors.
Which area of biology covers Regression Analysis, and how advanced is it?
Regression Analysis is one of the 51 topics in Lab Methods & Biostatistics. It is rated Advanced, so it suits learners who want specialist depth. Related topics in this area include Meta-Analysis, Null Hypothesis, P-Values and Multiple Testing.
Can you give an example of Regression Analysis?
Predicting blood pressure from age and weight.
What should I learn before Regression Analysis?
Work through the Beginner topics in Lab Methods & Biostatistics first, such as Scientific Method, Hypothesis, Variables, then return to Regression Analysis. Advanced topics assume the Intermediate vocabulary.
What topics are related to Regression Analysis?
The closest topics to Regression Analysis are Meta-Analysis, Null Hypothesis, P-Values and Multiple Testing, Experimental Design. Comparing them side by side is a good way to see how the ideas connect.
How can I check that I understand Regression Analysis?
Read the summary and the in-depth section, then use the quick check on the interactive lesson for Regression Analysis. To practise the whole of Lab Methods & Biostatistics, use the Lab Methods & Biostatistics quiz.
How is Regression Analysis different from Meta-Analysis?
Regression Analysis: Models the relationship between variables, predicting a response from one or more predictors. Meta-Analysis: Combines results from many studies to estimate an overall effect size. Read both side by side and note what each one explains.
How should I study Regression Analysis step by step?
First, read the summary and write the definition in your own words. Second, read the in-depth section and note any example. Third, compare it with Meta-Analysis and explain the difference aloud. Finally, take the Lab Methods & Biostatistics quiz and come back to this page for any question you miss.