How To Perform Simple Linear Regression In Excel

[@StevenBradburn]

ONLINE GUIDE toptipbio.com/linear-regression-excel/

[@mohitsingha1809]

Thanks so much.

[@divy03]

I loved the fact that, the content is so simplified and easy to digest

[@StevenBradburn]

Thanks mate appreciate the feedback

[@albertoclemente6071]

Finally a video that show in deeper detail all the coefficients and charts generated by Excel in a Regression analysis. Thank you very much for that.

[@marialavinia3365]

thank you so much! you did a better job at explaining than a lot of my teachers!!

[@benedictnuvye5277]

Very rare to find a video that is detailed and easy to understand like this one... superb indeed.

[@StevenBradburn]

Thanks for the feedback Benedict 👍

[@Ryan-nh3mt]

better job explaining this than a lot of other videos out there. good job

[@nasrollahrajaei4477]

Your teaching method, language, and presentation are just fantastic!

[@StevenBradburn]

Thanks very much for the kind feedback

[@pippinbloom]

Thank you so much for going through this in such detail. This was extremely helpful for me. I appreciate you!

[@RyanHolstad]

Extremely helpful, great example and well explained. It helped immensely with my Statics class. Thank you!

[@StereoMike06]

Thank you for this detail which is easy to digest. So many videos do not discuss the steps after the regression and how to apply back to your hypothesis and data plots.

[@subhadas9608]

Thank you very much sir for making this type of videos.... you don't know how much your videos helped others.... Your way of explanation is totally different from others and very easy to understand. Previously I had a lot of fear in statistics.. after watching your video I'm just loving stat...

[@リタンフランシスアグリーメントフェリック]

This guy has help me a lot after struggling on how to do this analysis on data.

[@David-lp1br]

Thank you for this detailed tutorial! The explanatory part was really helpful to determine which value was important in my research!

[@shubhamsirsikar1461]

Thank you for sharing such a detailed and high quality video.

[@mohitsingha1809]

Great explanation, this is the first really useful one for a novice to learn about how to interpret a simple linear regression model.

[@thebesttechnical3608]

Simple and easy to follow, thank you for this tutorial

[@gavinelias6272]

Solved my 10 day confusion in just 9 minutes

[@RoleJohn]

you rock Steven. you made me like it even more

[@jessicaescobar7549]

Thank you! one of the best tutorials videos i have seen. Very clear and practical.

[@MrKalerender]

Clean video on using that technique. Perfect for my students to refer to.

[@julescaruso4398]

Superb! This is excellent. Very much appreciate your in-depth coverage of each of the elements in the output

[@EnrqSan]

Best tutorial ever developed

[@anusingh164]

Thanks a lot. This video was very helpful if one wants to get a quick understanding on regression model .

[@epdelavega]

Excellent! Best linear regression video I have seen. Thank you!

[@StevenBradburn]

Thanks mate. Appreciate it 👍

[@hamayonkhaleqyar7286]

The best video for Regression ,1000000 likes

[@priyanshijoshi1394]

You are doing a great job. Keep it up 👍👍👍

[@adamrosen7937]

What a great presentation!

[@titantitus3133]

This is so helpful. Thank you so much! I am working on a research project and was having trouble getting started with regressions on excel

[@StevenBradburn]

You're so welcome! Good luck!

[@ngobamartyns-yellowe5555]

Thank you for sharing. Coming from a non statistical background, you really helped my understanding by the way you simplified the statistical analysis.

[@frosty20]

Thanks for the explanation i was struggling and i had to do a linear graph project with two varables of the topic NBA teams

[@StevenBradburn]

@@frosty20 very welcome!

[@maintainyoursanitywhenbein6660]

Thansk - very helpful ... I am going to watch many more of your videos ...

[@nkwanwighogomudonald5415]

Fantastic in teaching and explaining. GOOOOOOOOD JOB

[@Chic.Geek75]

Thank you for the most comprehensible piece, I am forever thankful!!!!

[@jainabatrawally7123]

This is superb 🎉. Keep up the momentum.

[@martinnhantran]

Thank you so much for the video. Simple and easy to understand.

[@jedrixmotovlog]

Man your explanation is very clear. Thank you 👌👌

[@StevenBradburn]

Cheers mate

[@loranscott3174]

This was a really great tutorial and very helpful.

[@evaschoenfeld3186]

WOW that video is super helpful, thank you so much for posting it.

[@kasmindanil5527]

this one is quite clear i found so far, thanks a lot sir.

[@somachisunday2967]

Thanks very simple to understand ❤

[@CLEFFJOE]

I just subscribed. Excellent video. Absolutely perfect analysis

[@StevenBradburn]

Cheers Jon Jon

[@saraparedes1666]

Thanks for this video! Helped me with a lab :)

[@potatotrash8320]

Thanks for this. This is a super big help.

[@StevenBradburn]

Very welcome

[@ThePokenger]

This was a lifesaver

[@bobmilani6109]

I'm a rock star thanks to you!

[@SaiVivekanandKuchimanchi]

SIMPLY WOW !!! . Can you suggest good tutorials for other ML models also pls like Supervised models (Classification models like Naive Bayes classifier, Decision Trees, Support Vector Machines, Random Forest, K Nearest Neighbours, Logistic Regression) (Regression models like Neural Network Regression, Support Vector Regression, Decision Tree Regression, Lasso and Ridge Regression) Unsupervised models (Clustering models like k-means clustering, mean shift clustering, DBSCAN clustering, Agglomerative Hierarchical clustering, Gaussian Mixture) Please brov. Thanks in anticipation.

[@prasadbishetti9879]

Thanks a lot for such clear explaination

[@vasiliostantanis4627]

Excellent job! Congratulations!

[@iamff]

Brilliant, just brilliant.

[@danielkwawuvi_tutorials]

detailed explanatory tutorial. thank you very much, Sir

[@mohitkaushik21]

Thanks a lot 😊

[@ramamohangadiyaram9004]

Excellent presentation Sir!!

[@StevenBradburn]

Thank you kindly!

[@benben7791]

Excellent video, thanks!!!

[@vascopatricio2]

Very clear, detailed and useful, super class. Thank you so much :-). Ps: (not randomly) subscribed.

[@StevenBradburn]

Thanks Vasco!

[@__Mako]

High quality explanation

[@HaciendoLQMDLG]

Very helpful video thank you so much!

[@davidkariuki3967]

Very helpful tutorial...step by step

[@kimwaters3140]

thank you, a thousand times, thank you, Dr. B, from a non-traditional (i.e., OLD) doctoral candidate dissertating in acoustic and socio-linguistics. Is that a Mancunian accent I hear, Oldham, perhaps? Peace, kw

[@williamodela]

This is helpful. Thank you, sir

[@NavaneethaKrishnanA]

Clear and Concise

[@clementn240]

thanks! great explanation!

[@mariamatunrase9312]

Very insightful ... thanks

[@SystemsProjectEngineer]

Excellent video.

[@gmanova]

superb little tutorial thanks.

[@becomingdr.e952]

Very helpful! Thank you.

[@mabvutobanda7699]

Perfect explanation

[@junisaresilvosa9430]

this is very helpful thank you

[@hichamitani6433]

amazing explanation prof

[@marcstla]

thank you very much! Very clear!

[@SunilPatil-tq5cb]

Hat's off to u sir for this great video

[@manuelgonzales2570]

EXCELLENT. Thanks!

[@Eric-yu1ur]

I really enjoy your video can you show us how to do a logistic regression please

[@michaelliu6323]

Thank you Steven for this great tutorial video! It is so helpful. Meanwhile, would you pls. explain why only the C.i. of the slope is considered to calculate the C.I. of the estimated y value in most textbooks? There are two parameters (slope and intercept) in the regression equation, and both parameters have C.I. calculated, shouldn't we put both C.I. into the calculation to estimate the CI of the y? thanks!

[@shankar167]

Top class video. Super like.

[@manishjargamagar9288]

Most useful. Thanks a lot

[@deividasbalt]

You are a god. Thank you!

[@DVGgames-od3tb]

Thank you so much!

[@noorakp9704]

This is easy to understand 😀

[@JD88784]

Great video

[@leahiennguyen8440]

very helpful, thank you!

[@MichaelMooreboston]

Hello Steve, at 6:53 area, I thought you would say you'd 'reject the null hypothesis', and not 'fail to reject the null hypothesis'. Possibly just a mix-up of words, but given that your p-value is less than alpha you would reject and not fail to reject.

[@gilbertsibwoga3619]

Probably a mix up of words

[@PrajwalKhanal-ox1is]

Thank you so much for such a wonderful video. May I have the excel file, so one can practice along with the tutorial.

[@ch4rs]

how goated this is my man

[@notmyrealname2.0]

Thank you!

[@neilsharma2793]

Thanks a lot man!

[@StevenBradburn]

Welcome mate!

[@amirahmanoar4462]

thank you so much

[@H.j.f.g.h.j]

thanks a lot? may God bless you.

[@NebiyouMaseboMalore]

Too interesting !!!!!!!!!!!!!!!!!!!

[@joselozano3105]

How come when I highlight the numbers with the labels it gives me, "contains non-numerical data?

[@antievtorduetrenchesvolley6658]

Very Clear

[@chukwuochachineduzim2497]

Please in l will need more tutorials on basic econometrics calculations and these type of vids....if not am failing this course please

[@thez00t6]

Much appreciated

[@Trigy100]

Very helpfull thank you

[@khudahafiz478]

Thank you so much

[@nishanthpillai6246]

If the significance F value would had been greater than 0.05..would the regression equation hence formulated be valid??

[@analynbautista2725]

Thank you

[@ginalam9543]

Hi, Can you run a regression when the y variable is a range and not a single number. For example range of income is the x variable and the years worked is the y variable

[@StevenBradburn]

Hi Gina Sounds like you need a logistics regression. With a logistics regression you can predict a categorical variable. However, I'm not sure how you do this in excel unfortunately

[@farhanchowdhury1846]

Thanks man

[@AKMKGP]

THANK YOU!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

[@NishanthPillaiOSCM-]

If my test is insignificant (Fstat