Statistics 101: Is My Data Normal?
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- Опубликовано: 6 июл 2024
- Statistics 101: Is My Data Normal?
Many statistical techniques assume that the underlying data is normally distributed. What simple techniques can we use to test this assumption? In this presentation we will briefly discuss the following tools to determine if our data is "normal" free of excess skew and/or kurtosis:
Histograms
Stem and Leaf Plots
Box Plots (Box and Whisker Plots)
P-P Plots
Q-Q Plots
I do not go into how these tools are calculated. This is merely an introduction to common preemptive visual techniques to determine the normality of a data set. Enjoy!
My playlist table of contents, Video Companion Guide PDF documents, and file downloads can be found on my website: www.bcfoltz.com
your intro make me feel calm because i'm struggling with spss right now.
I refer my friends and my girlfriend here whenever I'm stumped by statistics. I also appreciate the encouraging words at the beginning, you sir have that rare quality of encouragement that sounds genuine rather than condescending. Thank you for all your hard work.
Your videos are awesome. But kindly arrange them properly in playlists so that we can follow the videos sequentially.
Brandon, I suspect I fall outside the 'target audience ' that you imagine when you post these videos. I am a sixty-something machinist using S.P.C to try to control a C.N.C milling process. I found, much to my chagrin, that I need some grounding in statistics to draw useful inferences from my data.
Your videos were the best introduction to statistical thinking I found on the Web.
Good Work, in every sense of the words.
Thanks very much for doing these.
Mike...I could not agree more. Through Brandon I feel like I am rediscovering Statistics again...but now empowered to explore my own interests within what's being taught and my own curiosities.
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Just turned 60
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Look at the world around........
never too late to learn
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Thank you so much for your comment! :) I am very glad you found it helpful. All the best, B.
You are such a fantastic teacher .You explain so well even the finest details are clearly understood.Thankyou soo much . Please keep on supporting with your good work. God bless you !
+PradeepC Ghai Thank you so much! I've been fortunate to have great teachers my entire life. I just try to stand upon their shoulders.
Wow! You made me want to cry! I'm struggling with an online nursing research course and your introduction was the best peptalk I could have received! Thank you!
same here
Your insight towards making the data visual & then trying to explain the very purpose of the concept is amazing...You are the best mentor I have found in my life....Thank you Brandon
Hello, I just wanna say you are an excellent teacher and a wonderful person. not only are your explanations very easy to understand, but your motivational speech is inspiring. Thank you for sharing this!
I am not sure who are these 18 people who disliked this video. You are an awesome teacher. All your videos are great.
Thank you so much ..you are so supportive and encouraging.. I am so grateful to your kindness and great way of explaining all of these terms.
best channel to learn statistics for Machine learning
very helpful for someone like me trying to gain a foundation of knowledge to build on!
Very good video with very clear explanation and effective visuals. Thank you for taking the time to make these videos available.
You are the best explanation I have found. Great job.
Great content and explanation. Thanks!
For the first time I understand the different graphs in relation to probability. Thanks! KeepSmiling 😊🌺
Thanks Rahul! I am working on a new one right now on 2-Way ANOVA. With a full-time job and the complexity of the topics and work I put into them, they take a bit longer to make at the moment. But I am working on it! :) Best, B.
Great Video man. Clear and Informative. Thanks!
Thank you! Your videos are a GODSEND!!!!
impossible to teach better than this
Clear Explanation! Thank you Brandon.
Yes, thank you for that wonderfully motivating intro. You have no idea; my struggles.
Thanks for the great content and your encouraging words!! You are making me like statistics more.
Thank you so much for posting this. It was very helpful
Thanks a lot. Veeery useful, simple and clear. I wish i had had a teacher like you in my lycee. Good work.
Hi Brandon,
A lecture on how to find the best distribution for any dataset would be very interesting. Of course background of the dataset is more important to determine which distribution it follows, but finding best match distribution is still good for confirmation or exploration on not well-known data source.
Thank you for your help! Definitely helping me right now with my stats class!
Excellent Lecture. Thank you so much for your videos Sir.
Great series. I'm not sure why this video has been assigned to PL03 though. You start by mentioning all the other videos on the various probability distributions that you have made, all of which are in PL05 and PL06.
Thanks for the encouraging comments! They do not go unnoticed :).
Very nicely explained. Thank you sir.
Great video! Please keep helping us.
Best video on this topic!
Thank you for the video, and the nice words in the intro :)
Hi Brandon. You are a star. Thank you for your willingness help people like us. I like and appreciate the clarity of your facts/observations presented here.
Hi Brandon. Just a small query and will appreciate your observations. I have a large dataset for statistical analysis (specifically for ANOVA and linear regression) and currently wondering whether a visual idea of the p-p plot of the same is enough to analyze their normality. Is there any threshold statistic (a value) to consider for the plot to confirm normal distribution of the data? Many thanks.
Hi Brandon, you videos are great! May you let me know where I can find the Statistics 101 PL02?
The best stats teacher EVER!!!
I really like the way you explain material.
Brandon Foltz: great video! working on my M. S in biology and these videos are really helping me get through the initial stage of basic data analysis for my data!
its been 8 years how are you ??
Brandon, thanks very much for the videos, do you have one on percentiles?
thank you Brandon for research around the world who needs more statistics your product is useful. thank you again and keep it up
God bless you! Brandon you are better than Ivy league professors who have their videos uploaded. After all Teaching is more about communicating rather than demonstrating technical expertise ;)
Hello Brandon - do you have a video dedicated to q-q plots in the context of a simple linear regression between one independent variable and one dependent/response variable? Thank you.
I second this question! What does one do next if the data is not normally distributed?
Do you have a PL02 somewhere? I feel that I have missed some lessons but I cannot locate it on your playlists list! Thanks for your helpful videos.
Thanks for your videos, it helps :) and is easy to go to..
Keep up the good effort with sharing your knowledge.
I subscribed just because of that motivational speech at the beginning...Now to watch the lecture.
Agree With Mr Pradeep C Ghai. Watched your video today Only. It is great.
Thank you very very much for this great video.
Thank you very much for this informative video.
Excellent explanation of normality concept
Thank you! Simply Awesome videos. Pretty excellent explanation.
Thanks very much for your videos and making our life easier. Two quick feedback points:
The first video (Understanding Z-scores) in your list should be at number 4 on the list
The last (Is My Data Normal?) should probably move to another playlist (I guess at end of PL06 but please check as you are most familiar wit your lists)
Thanks
Sir thank you for all these videos
Simply Awesome.
Thanks a lot it's very helpful.. a question please..what do to if we have a bimodal distribution? can we make an AOV separately for each population.. And please can you make tutorials with R...Thanks!
such an inspirational introduction
Great work! Could you consider doing a video on half or folded normal? How do you work with bonded data i.e 0 and above? Thanks for your help
That intro made my day! ❤
Do you have a video on shapiro , kolmogrov tests etc.. i like the graphical inspection of the data
Hello Brandon, the fact of mean=media=mode can be used as guide to find what distribution follow our data ? I mean, as a first step for know what distributions we must consider or not consider? If yes, what can be the tolerance between them? Thank you for all your videos, they are very good and useful. Ivan Castilla
Really like your videos!! You say in this video that you will do a seperate video for p-p plots and q-q plots but i can`t find them :/
Sir
I m a big fan of urs. Really thankful to you.
But I find it a lil difficult to search in particular ur videos on a few topics..
U r the one who taught me stats...god bless you...
You're so sweet! The intro is awesome, I had to hear that m, thank u😣
Nice video. Thank you.
Thanks soo much Brandon!
Hi Brandon, I never leave messages usually but I just had to say thank you because this video is excellent. Very best wishes, Rebecca :)
Excellent!
+Shivaprasad Reddy Thank you!
i love you man. foreal foreal. God bless you!
Thank you!
VERY USEFUL.
Great video for ppl like me who have shallow knowledge about the topic.
Joarder Md Sarwar Mujib Thank you so much! Glad to have helped deepen your knowledge a little bit. But you took the time to watch and for that I am very appreciative. Best, B.
Well I gotta say that you helped me a lot with this video. Im on my Bachelorthesis and I write some critical words about the normal distribution and daily stock returns.
Now I plotted a lot of graphical stuff but i need some statistical tests. Do you have videos about the KS-Test, JB-Test and Hurst-Exponent. (interpretation and how it works) I have no statistical software. I have to work with excel.
thanks
regards from germany!
thx, this helped me a lot !
what kind/type of variables are we testing by using normality test please? i have so many and dont know which ones i need to test test. thanks
Thanks for sharing
You r the Best!
Great explanation. You speak loud and clear which made it very easy to understand.
Consider cutting some of your introduction. It was very long. Otherwise great job.
Thank you.
Pretty good, thank you
I am also looking for very simple 101 Statistics like these. Do you have a list of "order" of the video that I could watch. (I am 61 and just starting my PhD, it has been a long time since I had to do statistics.
Brandon,
I hear two mantras in stats that appear to oppose each other, and was hoping you could clarify: one is that it is very important to determine whether your data is normal, and the other is that because of CLT, it doesn't matter what kind of distribution the data comes from because the sampling distribution of the sample mean will be normal (given adequate sample size, etc.),
Am I misunderstanding something?
thanks,
Paul
You saved me bro.Thanks a ton from India.
You are welcome! But you saved yourself by pressing the play button. 🤟👊 Stay strong and keep learning. You got this.
Thank You!!!
THANK YOU
very good session
Great job again!! James N Zeris, CPA
thanks a lot .
thanks a lot a lot , you are amazing !!
What does the -3, -2,-1 represent on the X-Axis? Is it not the range ?
the most perfect video
can you do a video on linear programming?
why are the dots at the end of the whiskers not outliers? i thought all values beyond the box plot whiskers are outliers? or is that wrong?
great thanks
Hello! Unfortunately there is no easy answer as for what to do when the data is not normal (or why it's not normal in the first place). It could be because the population is not normal. It could be a sampling or data entry error (it happens). The sample data could be put through a transformation such as logarithmic. Different procedures have different tolerances for non-normal data. Non normal data is fine, it just depends on what you plan on doing next.
Hi, you are constantly talking about the "normality" of the data and that you should check if the data is normally distributed, BUT for the linear models, it is not necessary that the data is normal. It is about the errors that should be normally distributed for the inferential part. For example, in a t-test as simplest form of a lm, if there is a group effect, I would expect the data/dependent variable to be bimodal, so absolutely not normal. Or what do you mean by "data"?
please , what is the book you are explain ?
Hi Brandon, just want to comment that on the portion of stem & leaf and box plot. You said that "Median is pulled towards low end" --> this is mathematically not true because only the Mean or the Average of the data is pulled and not the Median which is always the middle data.
nice tutorial : )