Thank you for this video! I am a 4th year psychology student who put off taking the mandatory statistics course until the last possible second! So I sit in class, confused, with a bunch of 2nd year students every week. Online tutorials like this have been probably the only reason I've been getting marks in the 70s and low 80s so far. Good luck to every other math-hating student like me who has to take stats to get their degree!
I thought I was smooth sailing as I came to the end of my PhD program, but then I ran into the STATISTICS brick wall! What a nightmare this has been for me. I am so grateful that I have found your channel. You have such a way of explaining things. I am definitely going to subscribe! I have to be sure to watch more videos before dissertation time :(
Shalina Joy i am at the same place where you had been, the brick ball of surface response method and design of experiment part. The you tube tutorials with solved examples are infact a boon
I am studying a degree and my lecturer for research method only speaks with no visual ques which is not my preferred way of learning. You've literally turned a 1 hour lecture that confused me to hell into a 7min video that I 90% understood. thank you so much.
thank you so much for your videos. they are a wonderful addition to my biostats class for my masters in family nurse practitioner. so easy to understand and extremely well done. keep up the great work.
Thanks for posting these videos. They are super informative and clear. They are also always well-organized with a good structure and the content is always sufficient. Examples are useful as well.
anova method to compare the means of two or more groups, with t test we compare to more samples, in anova we have factors and level, like gender is a factor and male and females are levels. Some assumptions in anova is that the we have a normal distribution for the sample means, outliers are removed from the data set. Hypothesis in anova - Imagine having one factor with three level then is null hypothesis all the level are equal while alternate hypothesis is like not all factor are equal. when dealing with the effect of one variable is called the main effect. now two factor with three level then there are 3 sets of hypothesis null hypothesis all the level are equal for each factor while alternate hypothesis is like not all factor are equal for each factor. Then null hypothesis is two factor being similar alternate hypothesis is two factor are dissimilar. Interaction effect. So when you do plot and if the line cross each other then you can conclude that it has interaction effect. types of anova - one vay anova, one factor with at least two independent levels, repeated measure anova is one factor with at least two dependent levels(like measuring the people for something at day 1,2,3), factorial anova is two or more factors each having two level and the level can be dependent or independent or mixed(days 1,2,3,4 in columns and M & F as another level in rows ). When we reject the null hypothesis we are saying that there is a difference, but where is it. For this after anova is a done we have do post hoc analysis to find where the difference lies. While doing anova we calculate F statistics. If there is no difference between the factor or variable we expect F to be 1 if there is difference we expect F to be greater than 1. F statistics is always positive. so if F ratio< = 1 null hypothesis is true of f ratio is > 1 then null hypothesis is rejected.
WOW! I have sat through so many lectures not knowing what on earth my lecturer is talking about.... Thank you so much for your straight forward and simple explanation! Stats isn't that hard after all!
So what would rope hanging in the ocean and the amount of muscle growth on the rope for 3 seasons be? Would the rope be the factor? The muscles? Or the season?
Which ANOVA test needs to be done if I got a data set with 3 variables(Factor) with 4 levels. (ANOVA:Single Factor, ANOVA: Two-Factor with Replication, ANOVA:Two Factor without Replication. In Excel.
Hi sir, U lectures are superb and easy to comprehend. But I have a small suggestion that your speed is little bit fast. Sir your lectures are learnt by everyone worldwide so there are different people with different pronunciation. Hope you don't mind
Thank you for this video! I am a 4th year psychology student who put off taking the mandatory statistics course until the last possible second! So I sit in class, confused, with a bunch of 2nd year students every week. Online tutorials like this have been probably the only reason I've been getting marks in the 70s and low 80s so far. Good luck to every other math-hating student like me who has to take stats to get their degree!
I thought I was smooth sailing as I came to the end of my PhD program, but then I ran into the STATISTICS brick wall! What a nightmare this has been for me. I am so grateful that I have found your channel. You have such a way of explaining things. I am definitely going to subscribe! I have to be sure to watch more videos before dissertation time :(
This guy has a gift for explaining things (statistics) a gift even (some) top notch professors lack.
Shalina Joy i am at the same place where you had been, the brick ball of surface response method and design of experiment part. The you tube tutorials with solved examples are infact a boon
Yes, his voice is smooth, calming, and crisp. Good intonation!
it is...
Thank YOU, finally a video that gives a simple explanation.
I am studying a degree and my lecturer for research method only speaks with no visual ques which is not my preferred way of learning. You've literally turned a 1 hour lecture that confused me to hell into a 7min video that I 90% understood. thank you so much.
he turned my 2 and a half hr lecture into 7min video that I now understand better
thank you so much for your videos. they are a wonderful addition to my biostats class for my masters in family nurse practitioner. so easy to understand and extremely well done. keep up the great work.
Beautifully explained! I am taking my Six Sigma Black Belt Certification Course and just saw some of your lectures. You have a great teaching talent!
Thanks for posting these videos. They are super informative and clear. They are also always well-organized with a good structure and the content is always sufficient. Examples are useful as well.
That was so good! The organization of it all! Thank you!
I am so thankful for you sir .. You are so brilliant , I learned a lot.. God Bless you. May have long long life ahead...
This is “short, but powerful” like we say in Dutch. Thank you for this clear video! 👌🏼
feebee1982-You are awesome, you make dinkys happy
anova method to compare the means of two or more groups, with t test we compare to more samples, in anova we have factors and level, like gender is a factor and male and females are levels.
Some assumptions in anova is that the we have a normal distribution for the sample means, outliers are removed from the data set.
Hypothesis in anova - Imagine having one factor with three level then is null hypothesis all the level are equal while alternate hypothesis is like not all factor are equal. when dealing with the effect of one variable is called the main effect.
now two factor with three level then there are 3 sets of hypothesis null hypothesis all the level are equal for each factor while alternate hypothesis is like not all factor are equal for each factor. Then null hypothesis is two factor being similar alternate hypothesis is two factor are dissimilar. Interaction effect. So when you do plot and if the line cross each other then you can conclude that it has interaction effect.
types of anova - one vay anova, one factor with at least two independent levels, repeated measure anova is one factor with at least two dependent levels(like measuring the people for something at day 1,2,3), factorial anova is two or more factors each having two level and the level can be dependent or independent or mixed(days 1,2,3,4 in columns and M & F as another level in rows ).
When we reject the null hypothesis we are saying that there is a difference, but where is it. For this after anova is a done we have do post hoc analysis to find where the difference lies.
While doing anova we calculate F statistics. If there is no difference between the factor or variable we expect F to be 1 if there is difference we expect F to be greater than 1. F statistics is always positive. so if F ratio< = 1 null hypothesis is true of f ratio is > 1 then null hypothesis is rejected.
thanks for the introduction thats what i was in need for
WOW! I have sat through so many lectures not knowing what on earth my lecturer is talking about.... Thank you so much for your straight forward and simple explanation! Stats isn't that hard after all!
Thank you for making this video. it was very informative
So helpful! THANK YOU!
These videos are awesome, thanks!
Hey very good lectures. Can I know what reference books are you using in learning statistics? Thanks.
how can i get the null hypothesis from anova table
You are amazing! Thank you !
Thank you. Great explanation.
big thanks from my heart
tysm, it was very good and clear video. i understood the overview of the content well.
I didn't get the calculation of sum of squares between the groups..my squares r coming diff. how come 40.7 multiplied by 5 equals to 203.3?
Super clear! Thanks!
Awesome, straight to the point 👍🏽
it helps a lot. thank you so much.
Thank you sir so much....what a video....
Excellent !!
The pdf or ppt of these lectures will be very helpful.
So what would rope hanging in the ocean and the amount of muscle growth on the rope for 3 seasons be? Would the rope be the factor? The muscles? Or the season?
Great video THANKYOU 😇😇
Thank you!
Which ANOVA test needs to be done if I got a data set with 3 variables(Factor) with 4 levels. (ANOVA:Single Factor, ANOVA: Two-Factor with Replication, ANOVA:Two Factor without Replication. In Excel.
...very informative. I actually understand.
So helpful!
It Really helpful Thankssss
Thanks a lot.🙏
Hi sir, U lectures are superb and easy to comprehend. But I have a small suggestion that your speed is little bit fast. Sir your lectures are learnt by everyone worldwide so there are different people with different pronunciation. Hope you don't mind
thank you post this video
It's cool. Teaching Stats in a simple way...
Thank you
This was great!
Oh my GOD, I had no idea that stats could make sense.
Hello. If our hypothesis was "Ho: μA1 = 5", what would our solution be? (That is, judging by its equality to any number.)
Good one
excellent :)
im still lost on the f-statistic :(
the dependent and independent variable part so confusing..
you're good
your content is really very good but the speed is very fast for beginner.
+tushar modi Pause the vid, take notes and research on google. It's perfect speed.
This is exactly what I do! Sometimes you need the person to repeat it again and again until you get it.
hi, I'm nena and OMG I GET IT... and I never understand anything in stats.
good presentation, but is to fast for beginner bro
Great
I think F should be F = treatment differences / random differences
ANOVA compares the means of three or more groups, not two or more. Other than that, great video.
As far as i know, eventhough t-test are more preferable and commonly used for two groups.. Anova can be used too
Bro you sound like Michael Cera
2024 team where you
this was filed in 2010 when we only had two genders
gender is a bad example for factor in ANOVA as it considers more than two means(levels),
Male and female. Where there is physical or psychological confusion, those people should not be selected for the study.
@@KJKP yes you are right
Here's the asian ruin it for everyone who barely understands with the.. whatever it is. JK