Define what a confounding variable is and provide a brief descriiption of the study.
Discuss possible confounding variables that could be considered as influencing the response variables within the study.
Explain how important it is to consider confounding variables when measuring data. Should they be weighed heavily when it comes to results or be less of a consideration when looking for correlations between variables? Support your reasoning. No title page needed, able to copy and paste to discussion board in class. Also Look at the information downloaded with assignment Regression and R-Squared (2.2) (Links to an external site.)
How to calculate linear regression using least square method (Links to an external site.)
Least Squares Regression Line on the TI83 TI84 Calculator (Links to an external site.)
Introduction to residuals and least squares regression | AP Statistics | Khan Academy (Links to an external site.)
Residual plots | Exploring bivariate numerical data | AP Statistics | Khan Academy (Links to an external site.)
Here’s a list of helpful resources to learn more about the subject:
Lumen Learning: Chapter 7 – Correlation and Simple Linear Regression (Links to an external site.)
The Coefficient of Determination, r-squared (Links to an external site.)
Libre Texts: The Least Squares Regression Line (Links to an external site.)
Inference for Bivariate Data (Links to an external site.)
Interpreting Residual Plots to Improve Your Regression
