Once you get the slope (^a) you don't really need the formula to calculate the intercept (^b). Just use the mean values of x, y and plug the slope in the line equation: y_mean = ^a * x_mean + ^b. Here, we have, y_mean = 20/6, x_mean = 19/6 and slope(^a) = 0.9324. So, we get intercept (^b) = y_mean - ^a * x_mean = 20/6 - 0.0324 * 19/6 = 0.380733
Please solve this question- Consider the linear regression model y = - 1.5x + 5.6 + e, where e is a normal random variable with mean 0 and variance O ^ 2 = 4 Determine the mean and standard deviation of when x = 2 and x = 4.5
Say for example Y = number of rooms. And we get Y=1.234 from the regression line for a certain X value. How can we mark this on our scatter diagram? Is it 1 because "number of rooms" cannot have fractions? Or do we mark the exact value we get?
Thank you for posting this example of the correlation and Linear Regression. My question is this, can you please show on the calculator how you came up with the answers to the equation? I've tried to use my own calculator to see how you came up with the answer and have had no luck. I keep coming up with the incorrect answer.
Nice video Its great But there is a little bit mistake that you made, when you was finding a^ instead of putting value of submission(xy) you put value of x square. Again thanks for this good video!!!
Isn't that the general idea behind a prediction -- NOT knowing the outcome? How would you ever get a strong (or ANY for that matter) linear relationship exceeding the measured values? Great video by the way! Thanks for putting this out. :)
hey thanks you really helped me with the work i needed to get done because the formula the prof gave me would not give me the answers i needed and yours did so thanks alot
it seems that the formula used to calculate constant a is that could be used for b, the lecture should check, otherwise we should be confused or taking wrong lesson
what is the relationship between correlation and regression? is it correct to say that if two variables are strongly correlated then linear regression analysis can be used to predict the value of independent variable?
I think the formula of Standard Deviation is not correct. The denominator must be N instead of N-1, since we take the square root of the average of the squared differences from the mean. Anyways, great video! Helped me a lot.
+Keval Sheth With N-1, we have an unbiased estimator of the variance. This means that the expected value of s^2 (the sample variance) is sigma^2 (the population variance). With N, the estimator is biased, which is less desirable. (This is not obvious at first glance.)
Research by Huhtaniemi et al. (A-19) focused on the quality of serum luteinizing hormone (LH) during pubertal maturation in boys. Subjects, consisting of healthy boys entering pubeny (ages 11 years. 5 months to 12 years), were studied over a period of 18 months. The following are the concentrations (TUL) of bioactive LH (B-LH) and immunoreactive LH (1-LH) in serum samples taken from the mbjects. Only observations in which the subjects' B/ ratio was greater than 3.5 are reported here Can someone please solve it
The sample standard deviation is divided by n-1. The reason is that it makes the sample variance an unbiased estimator of the population variance. This means that the expected value of s^2 is equal to sigma^2. Always be careful differentiating between the sample variance and the population variance.
Hello please you gave out two formulae for the standard deviation. But the answers varies. Can you please explain further. Am confused with the other equation
Wait.... so why didn't you multiply the equation of the least square with 4.5 for y? You multiplied 5 for x but not y, You subtracted.... Do you understand what I mean?
hye Prof..if u don't mind....just quick question..le my independent was extraversion n my independent was birth order with 3 category under it like 1st,2nd n 3rt order...let say if I want to measure which birth order is more extraversion can just run it by using this linear regression?
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sometimes old fashioned pen(cil) and paper works best! thanks for breaking linear regression down to its most simple components
Your pace, accent, method is sooo good that makes you're the best teacher thank you
Your teaching is so perfect and the pace is so good. You are a good teacher. Thanks so much
Very nice and straight forward. Will have to calculate coefficients and linear regressions within my finance class, this really helps.
I hate school.
sorry
😢me too 😅
Sameeee
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merci beaucoup mister ❤, love youuu, from naina
You are the best tutor. Statistics made easier. thank you
You made it very simple . A great teacher you are . Much appreciated
I highly appreciate this effort I hope that you will upload more of these in order to help students improve the acute in correlation coefficient
Amazing. Helped me with my Uni assignment.
Much love.
THANK YOU FOR YOUR CONCERN FOR OUR STUDIES
If only they’re this good at teaching us thanks for this masterpiece I appreciate it
your one of the greatest teachers... so much i appreciate your work
I couldn't find a enoug tutorial which one is enough to explain regression until now, I really understand all of them, Thanks sir !
You have a very clear voice which gives people morale to keep listening as they learn.Thank you
Thank you so simple! Even those who problem. Of easily catch up can understand this
You are far better than my lecturer thank you sir
Once you get the slope (^a) you don't really need the formula to calculate the intercept (^b). Just use the mean values of x, y and plug the slope in the line equation: y_mean = ^a * x_mean + ^b. Here, we have, y_mean = 20/6, x_mean = 19/6 and slope(^a) = 0.9324. So, we get intercept (^b) = y_mean - ^a * x_mean = 20/6 - 0.0324 * 19/6 = 0.380733
thanx very much its my last year in college and your lesson helped me thanx again :)
It's very much clear to undestand easily. lots of thanks to your effort.
Please solve this question-
Consider the linear regression model y = - 1.5x + 5.6 + e, where e is a normal random variable with mean 0 and variance O ^ 2 = 4 Determine the mean and standard deviation of when x = 2 and x = 4.5
I can't believe I struggled with this topic this semester, thanks for the video, ready for my final exam 😁
Sorry how is life now. You are done with university 🎉
Thank you kind sir, your effort made my day, by explaining me this in a cristal clear manner.
you made this SO easy, my GPA thanks you
Very brilliant teacher. Summarized piece of work and clear to the point. Thank you so much 🙏🙏🙏
Glad it was helpful!
You're too much.. I'm falling in love with economics again
Best long math video I’ve seen so far
Say for example Y = number of rooms.
And we get Y=1.234 from the regression line for a certain X value.
How can we mark this on our scatter diagram?
Is it 1 because "number of rooms" cannot have fractions?
Or do we mark the exact value we get?
Allah makes the impossible possible.
this video is really helpful for my final test tomorrow lol thank you 😃
same here lol :)
haha tommorrow iz my final exam....😅😅
haha kesa huva phir? hahah
one of the best ....many thanks for such a clear explanations
thank you for giving us these tutorial, we really appreciate them.
excellent teaching. very easy to digest. thanks
This was a wonderful video thanks for helping me get an A on my Stats Midterm!
wonderful...all tackle my paper for tommorrow with alot of ease....thanks teacher
Great video slcmath, different from other methods, very interesting esp getting the linear regression first.
Thanks for helping me with my studies
Brilliant!!!!! This video really helped me out. i was in class last week and didnt understand a thing but this Thumbs up
This is very nicely explained and a very nice pace......easy to follow..
Thanks for this simple and clear video
You are incredible!! Now I understand regression
Every single video I find on this topic that uses these formulas calculates E(y ^ 2) but then doesn't use the result anywhere.
Thank y so much.
Can y please make a video about logistic regression.
Watching this to understand our lesson in modular classes💜
Thank u for this one✨ really appreciate this
very nice and very clear
Straight to the point. Thank you for sharing.
Great explanation! Thank-you!
Thank you for posting this example of the correlation and Linear Regression. My question is this, can you please show on the calculator how you came up with the answers to the equation? I've tried to use my own calculator to see how you came up with the answer and have had no luck. I keep coming up with the incorrect answer.
Nice video Its great
But there is a little bit mistake that you made, when you was finding a^ instead of putting value of submission(xy) you put value of x square.
Again thanks for this good video!!!
Isn't that the general idea behind a prediction -- NOT knowing the outcome?
How would you ever get a strong (or ANY for that matter) linear relationship exceeding the measured values?
Great video by the way! Thanks for putting this out. :)
Wondering if you ever got your answer, as this was commented 8 years ago. I'm having the same question now
hey thanks you really helped me with the work i needed to get done because the formula the prof gave me would not give me the answers i needed and yours did so thanks alot
Thanks you have helped me
Thanks you have helped me
At first I thought Ross from Friends was giving the lecture!
Lmao
i watching your vidio make me relly bunderstand very clear,,
Man your stuff is really good
Great. . it helped me for my exam... Thank u...
wow....this is the best video explaining these topics
Thank you very much, very clear explanations make the whole video worthy to keep and share.
***** hi how are you??
Vivek Negi not here pls
same here lol
thank you so much for this it will be really useful for my final exam
Your writing is very nice visually and the explanation is quite good as well :)
yes his handwriting is good
Thank you for sharing this great tutorial !!
Thanks for your best explanation.
That was incredible. Thanks so much
Good....👍
tamammm videio sireee
it seems that the formula used to calculate constant a is that could be used for b, the lecture should check, otherwise we should be confused or taking wrong lesson
Everything presented is correct. :-)
Amazing video ! Helped me to brush up my concepts ! Keep up the good work :)
I wish you were my lecturer
You are the best . Thanks a lot 🙏
That was a brilliant and beautiful explanation of a complicated process!
Very well explained! Thank you
good video, thanks for sharing
thanks for your teaching.
Fantastic video, thanks for this
what is the relationship between correlation and regression? is it correct to say that if two variables are strongly correlated then linear regression analysis can be used to predict the value of independent variable?
Thank you dear, you really saved me!
Very useful thank you so much
Can the answer be correct if my x value is 3?
Thanks really helpful
I think the formula of Standard Deviation is not correct. The denominator must be N instead of N-1, since we take the square root of the average of the squared differences from the mean. Anyways, great video! Helped me a lot.
+Keval Sheth With N-1, we have an unbiased estimator of the variance. This means that the expected value of s^2 (the sample variance) is sigma^2 (the population variance). With N, the estimator is biased, which is less desirable. (This is not obvious at first glance.)
n-1 is used for sample while N is used for population.
Thank you. This is very helpful. The video explain y on x. how do you find out x on y?
If y=mx+b, then solving for x yields x=y/m -b/m.
This video helps a lot for my final tomorrow. Thank you!!
Research by Huhtaniemi et al. (A-19) focused on the quality of serum luteinizing hormone (LH) during pubertal maturation in boys. Subjects, consisting of healthy boys entering pubeny (ages 11 years. 5 months to 12 years), were studied over a period of 18 months. The following are the concentrations (TUL) of bioactive LH (B-LH) and immunoreactive LH (1-LH) in serum samples taken from the mbjects. Only observations in which the subjects' B/ ratio was greater than 3.5 are reported here
Can someone please solve it
Thank you very much. It was very helpful
why you not plot a graph ?how we indicate the regression relationship ? 😒
can i ask if the summation will not be divided by the total number of values ?
Is regression and linear regression the same thing and correlation and coefficient of correlation?
Super helpful. Thank you.
This is SO helpful
thank you for sharing this video. Incredibly helpful
Can u do multiple regression?
The formula for standard deviation has n-1 in denominator which is wrong. It should be n
The sample standard deviation is divided by n-1. The reason is that it makes the sample variance an unbiased estimator of the population variance. This means that the expected value of s^2 is equal to sigma^2. Always be careful differentiating between the sample variance and the population variance.
Well explanation
This is crystal clear...Thank you..=D
great content
When can i use the deviation forms of the equations to estimate
Hello please you gave out two formulae for the standard deviation. But the answers varies. Can you please explain further. Am confused with the other equation
Wait.... so why didn't you multiply the equation of the least square with 4.5 for y? You multiplied 5 for x but not y, You subtracted.... Do you understand what I mean?
Thank you so much for this video
hye Prof..if u don't mind....just quick question..le my independent was extraversion n my independent was birth order with 3 category under it like 1st,2nd n 3rt order...let say if I want to measure which birth order is more extraversion can just run it by using this linear regression?
Is it possible for your standard deviation to come out negative
No.
You're a god. Thanks man. I had the wrong formula the entire time lol!