These are just a few examples of what the research questions and hypotheses may look like when a regression analysis is appropriate.
Simple Linear Regression
- RQ: Does body weight influence cholesterol levels?
- H0: Bodyweight does not have an influence on cholesterol levels.
- Ha: Bodyweight has a significant influence on cholesterol levels.
- RQ: Can IQ be used to predict GPA?
- H0: IQ does not predict GPA.
- Ha: IQ is a significant predictor of GPA.
Multiple Linear Regression
- RQ: Do oxygen, water, and sunlight influence plant growth?
- H0: Oxygen, water, and sunlight are not related to plant growth.
- Ha: At least one of the predictor variables is a significant predictor of plant growth.
- RQ: Are IQ and gender useful in predicting GPA?
- H0: There is no relationship between IQ or gender, and GPA.
- Ha: IQ and/or gender significantly predict(s) GPA.
Logistic Regression
- RQ: Can you predict a person's gender based on income?
- H0: Income is not a predictor of gender.
- Ha: There is a predictive relationship between gender and income.
- RQ: Do customer satisfaction, brand perception, and price perception influence purchase decision?
- H0: There is no relationship between customer satisfaction, brand perception, price perception, and purchase decision.
- Ha: At least one of the predictor variables has a predictive relationship with purchase decision.
Multiple Logistic Regression
- RQ: Do standardized test scores in math, reading, and writing, influence game choice?
- H0: There is no influence on game choice by standardized test scores.
- Ha: There is a significant influence of at least one of the predictor variables on game choice.
