SAS Tutorial | Simple Linear Regression in SAS
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- Опубліковано 1 сер 2024
- In this SAS How To Tutorial, Andy Ravenna discusses how to perform simple linear regression in SAS. Linear regression is used across a wide range of fields to help predict a continuous target variable, something like “sales,” for example. Input variables are used to help predict the target variable. In simple linear regression, only one input variable is used to predict the target variable. Andy begins by exploring the formula for linear regression. Then he discussed ordinary least squares regression, which is how the parameter estimates are calculated. He’ll then demonstrate simple linear regression two ways: using SAS Studio and in SAS Visual Statistics, using SAS Viya.
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Bank data can be found in the SAS Visual Data Mining and Machine Learning Free Trial - www.sas.com/en_us/trails.html
Chapters
00:00 - Simple linear regression explained
07:36 - Demo: How to perform simple linear regression in SAS Studio
24:44 - Demo: How to perform simple linear regression in SAS Visual Statistics, using SAS Viya
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SAS Video Tutorial: Simple Linear Regression Using SAS® Studio - video.sas.com/detail/video/33...
◉ SAS Video Tutorial: The Generalized Linear Models Task in SAS® Studio - video.sas.com/detail/video/55...
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Hi!
Thanks for checking out my video on simple linear regression in SAS. Let me know what you thought and if you found it helpful. Also, let me know if you have any questions. Have an awesome day!
Andy
You are an incredible instructor, thanks.
We appreciate your feedback and thanks for tuning in!
Greate Explanations on how to do reg. in SAS also you explained the concept of reg. in vary simple mannar.
thanks.
So glad you found it helpful!
Thank you, Satish!
Best part about your videos, you don’t bore while making these informative videos.
Glad you think so! We hope you'll come back for more!
This is the best SAS viya tutorial I've seen! please do more!!
Excellent! Glad to hear this tutorial was helpful to you! You can also find other helpful support resources on SAS Viya on our support pages 2.sas.com/6054H8pnM
Thank you, Rachel!
Excellent Explanation. Just what I was looking for. Thanks Andy!
We're so glad you found the tutorial helpful! 🙂
Thank you, Yuri!
Excellent presentation Andy! I wish I learned about SLR like this, you break it down so well! Thanks!
Glad you enjoyed it!
Thank you, Kriss!
excellent sharing...I like it alot...Gonna explore more videos after this!!!!
Thank you for sharing your feedback!
Great Video Andy!
Thank you, Sathish!
You are great in making thingd understandable. You spkoe very clearly and at the perfect pace.
Thank you so much for the feedback, Alakh!
Thank you, Alakh.
best SAS explanation for linear regression
Great! Thank you for your feedback!
Thank you, Sarah!
Yeah he’s a talented educator and friendly. Rare for statisticians ;)
Just kidding. Those are mathematicians lol
Thank you for the tutorial.
Excellent presentation sir
Thank you for your feedback!
I don't have access to SAS yet but this is really helpful. Thank you for putting this out!
Absolutely!
This video exceeded expectations! thanks a ton!!
Thanks for sharing! We're so glad you enjoyed the content.
Thank you, Excel!
thank you M. Andy I appreciate your videos
You are very welcome and thanks for posting!
Thank you, Skandar!
I like the idea (I did not watch the entire video because I feel I already know linear regression) and I especially like that it was posted over at SAS Communities (but I'm not allowed to comment on the post there, so I comment here). SAS Communities needs more basic statistics and basic programming tutorials; there are plenty of tutorials that appear at SAS Communities on advanced topics like Hierarchical Models and Quadratic Discriminant Analysis and so on; this is the first I have seen at SAS Communities on basic statistics. Furthermore, there needs to be some mechanism to search for tutorials at SAS Communities (if there is such a mechanism, I am not aware of it) and there also needs to be some mechanism to search for VIDEO Tutorials at SAS Communities. And maybe even post a comprehensive list of all such video tutorials at SAS Communities (and keep re-posting the list every week, because there are always new people joining, or searching for something).
Thanks for the feedback Paige! We have a big list of topics to cover in this format. If you have ideas for the top statistics topics to tackle first, let us know!
Hi there Paige, we hear you on adding a mechanism to find video tutorials on the SAS Communities and are exploring ways to do that. Thanks for your input!
@@chrishemedinger1382 can you please do a multiple linear regression including interaction/ effect modification, then latent class analysis, trajectory analysis. Thanks!
@@nnette21 Good suggestions -- we have a steady stream of new topics coming, so stay tuned! I'll pass your ideas on to the team.
Thank You for the clarification.
Thank You for a great explanation sir...
We appreciate your feedback! Glad you found the explanation helpful! 👍
Thank you, Nav!
Excellent
Thank you, Shekhar!
Thanks
Thank you, Aniruddha!
I think there is a mis-statement at about 13:20 of the video:
"P-value very small tells me that this model is doing a very good job at explaining a lot of the variability of the target."
But that's not what the p-value tells you. It tells you that the fitted line is statistically significant, or in layman's terms that the fitted line did not happen by random chance. The r-squared tells you when the model is fitting a lot of the variability. You could have a p-value of 0.001 and a low r-squared, indicating that the fitted line is statistically significant but it does not explain a lot of the variability of the target. These concepts should be intertwined as the speaker said.
Hi Paige, I wouldn’t disagree with you. I made quite a few leaps for that general statement, but I was trying to avoid a deep down discussion for this video. The p-value for that ANOVA table in a linear regression is a test of the null hypothesis (that all the regression coefficients are 0; in this case we only have one.) A very small p indicates that we found evidence that at least one of our coefficients was non-zero. You can then look at the table of the parameter estimates to see that the p-values for both the y-intercept and our one term were also very small (also indicating evidence of being non-zero.) Thus, we found some inputs that appear to be statistically significant. I probably meant to throw in a small discussion about the r-square value, which is a much better statistic and indicating that the model is explaining the variability in the target. Thanks for catching that!
andy, in your last model, the r square is 0.0914, how do you explain that small R square?
John, thank you for your inquiry! We are checking on this for you!
Hi John, thanks for your question. At time stamp 28:51, take a look to the right of the R-Square. You'll notice that out of approximately 1 million observations, only about 20% (211,509) are used in this linear regression. In this VS_Bank table, non-purchases are coded as missing for the target tgt Interval New Sales. So basically, this linear regression is only using 20% of the original data. I think this is the best explanation for why that R-Square is so low. I hope this helps! Thanks, Andy
@@andyravenna4222 thanks for replying. I am a new student to linear regression and SAS. So based on your explanation, if the data is cleaned by removing empty sales, the RSquare will increased?
@@heahkl Hi John, it is great that you are so interested in Linear Regression. Since you are new, I'd like to encourage you to take our Statistics 1 course: support.sas.com/edu/schedules.html?crs=STAT1&ctry=US . It is an Introduction to ANOVA, Regression, and Logistic Regress. To get back to your new question, it turns out that this particular data table has already been cleaned. Because those sales values are missing, they are ALREADY being removed from the Linear Regression. If you are looking for ways to increase the R-Square, we would have to consider other alternatives, such as adding interaction terms or considering an alternative model. The Statistics 1 covers a lot this. I hope this helps! Thanks, Andy
They gotta stop making you guys wear those Walmart blue polos 😂💀
We might argue that they're "SAS Blue" polos 😉 Either way, thanks for tuning in!
"Simple"....Typical with SAS. NOTHING is simple. Everything is super complicated. More info than you need and all sorts of exceptions and that you just have to "know".
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