Statistics 101: Multiple Regression, Stepwise Regression
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- Опубліковано 27 лип 2024
- In this Statistics 101 video, we explore the regression model-building process known as stepwise regression. This is done through conceptual explanations and by analyzing computer output from JMP. Enjoy!
My playlist table of contents, Video Companion Guide PDF documents, and file downloads can be found on my website: www.bcfoltz.com
JMP by SAS: www.jmp.com/en_us/software.html
Happy learning!
#statistics #machinelearning #datascience
Very helpful content Brandon. Thank a lot and keep it coming
Thanks, Brandon. Finally, the man behind making statistics easier than ever is on screen. Awesome conetent. Keep making more.
More to come! I have a face for radio. 🙃
I never left Brandon! You are literally taking me through my doctoral program, my comprehensive exam and chapter 3 of my dissertation!!! Thank you, thank you, thank you!
You are very welcome Desna. I know you will do great, Dr. Jackson-McDonald.
The man behind the screen! Best video EVER!
Thank you for making the course of statistics so amusing !
Thank you! I'm not working on a project at the moment but I value the lesson.
I can't thank you enough for these videos. I've used these so much to learn and teach my own students ♥
Thank you for great videos!!
Your content and explanation is very powerful. Highly appreciate your effort for providing such a valuable output for us. Just was wanna thank my heart. Will always stick to your channel to learn statistics
it took me 2 sec to subscribe you .... ur nameste took my attention
Thank you so much. This helped me a lot.
Hi, great series! Thanks a lot! Do you btw have any tips for a feature selection technique that selects covariates/features as long as the increment in R^2 is larger than delta ? Thank you.
Thank you professor
Hi Brandon, Thanks for the wonderful video. However, I have a doubt related to entry and exit of a predictor variables. For entry and exit of a variable do we have to look at the p value related to F statistics ( for the entire model) or p value related to t test ( related to individual variable) ?
I have exam on this tomorrow, and you coincidentally uploaded it today
Awesome. Now go kick ass. 👍
Hello, I work with five regressors, I can build linear models using "lm", however, I haven't identified a package that does StepWise when some data is missing from one or another variable, making me sacrifice data from individuals who don't have all the measures . I've already used the methods in the stats and StepReg packages without success
Hi Brandon, do you recommend testing each variable's relationship to the DV first, like say using T-test or Anova before considering using them in your model? And if so, do you have a video on this? Thanks!! I love your videos!
his earlier videos touched on this. you may check his playlist on regression topic on his channel.
hello Brandon do you solve multiple regression in excel ? can you mention the steps involved.
Very helpful content Brandon. Thank a lot and keep it coming (could you please, focus on the interaction between variables and the difference between interaction and the multicollinearity how we can eliminate it in a separate video)
Can step-wise regression be used for research studies of social science??
please reply asap
I'm a just now learning this to analyze chemical systems and engineering equipment, is this really considered basic statistics?
Hello! Yes, you will find model building methods in introductory statistics books. It would be considered "second semester" content but it is part of intro stats.
Hi Brandon, your videos have been the most helpful on UA-cam. However, I think it's less distracting not to see the voice owner...we got far too used to your earlier way of presenting.