Unlock the Secrets of Multiple Regression with Expert Guidance and Real-World Application

Recent questions in Multiple Regression
Inferential StatisticsAnswered question
shiya43 shiya43 2022-10-29

Can you use bivariate analysis in a multiple regression problem
I have one response variable and around 10 potential explanatory variables. I am looking for simple ways to visualize and explore my data before modelling. As well as carrying out PCA and looking for correlations between my explanatory variables I wanted to look at bi-variate scatter plots of the response with each explanatory variable - but I have been told this wont work.
This is they way I am picturing it -
Imagine you have n independent, uncorrelated explanatory variables.
You propose to use these variables in a multiple regression. You want to simplify the analysis by not including more variables than is necessary.
So , you want to know if the explanatory variables have any correlation with the response variable to decide whether to include the variable in the regression.
My feeling is 1) that you can look at bi-variate plots for the response variable with each explanatory variable to see if there is a correlation.
2) If a single explanatory variable has no correlation with a the response in bi-variate correlation, it cannot have any affect on the response if included in the multiple regression.
(The only way this variable could affect the response variable would through an interaction with another explanatory variable - but it has already been determined that all the explanatory variables are uncorrelated.)
I have been told that the above is incorrect and a variable showing no correlation in a bi-variate plot can affect the response variable in a multiple regression.
Could someone help me see where I am going wrong? Many Thanks.

Inferential StatisticsAnswered question
Charles MugishaCharles Mugisha2022-09-21

Multiple regression is a form of predictive analysis used to measure the impact of multiple variables on a desired outcome. It is a powerful tool for data analysis that can be used to determine how much effect each variable has on the outcome. This technique can be used to identify relationships between variables, develop predictive models and measure the impact of changes in variables. Multiple regression can also be used to assess the impact of different factors on a given outcome and help to develop strategies for improving outcomes. By understanding the relationships between different variables, businesses can apply multiple regression to help make better decisions and improve their operations.