Hello I just wanted to comment that your videos has helped me understand business statistics better and made me love learning it. As I religiously watch your videos before every business statistics lessons I have, I get very excited to learn and I haven't felt that about studying in so long and I'm really glad your videos helped me gain that back. I want to thank you for the examples and explanations and for helping me get straight As 😂. I've never felt so accomplished in my life before and it's my proudest achievement. Thank you. 😊
For anyone who's curious the correct row totals are 270 for boys and 230 for girls. After similar calculations to those in his video, the chi-squared value is 259.796. So you still reject the null hypothesis.
@DonZaka93 The problem is wrong, the way he works on it is right but the mistake was when he added the totals of the observed values, he set 300 and 200, when in reality the totals are 270 and 230 (therefore screwing up the calculation of expected values, and result of x2)
This video confused me so badly. I had no idea where his 276.389 value had come from T^T.. Thank god for the comments saying that the correct x^2 = 259.796 because that is what showed up on my calculator :)
Can we use Chi-squared when we have more than 2 classifications such as Male Females and Trans? So the degrees of freedom will be (3-1)*(3-1) = 4 Is that right?
Honestly, i dont get how my statistics Professors could make something so seemingly easy that complicated. I mean, ive learned more in 4 minutes here than in 20 minutes in university
I always supplement what I learn in university with videos like these. Its always good to get multiple perspectives of a concept, which greatly helps you understand it better.
Thank you so much, I know that there is a mistake in the marginal frequencies but it does not interfere in the way you explain it. It is very helpful! Thanks
Hi, quick question, why you used that Null Hypothesis as not related (gender and favorite color) when mostly in statistics the Null hypothesis for equal, and alternative for not equal, more or less?
you mean, that the observed value is similar to the expected value? Because i can't see how you could relate the chi-square test to this problem. I would use the double sample t-test. We are expecting that the number of male students is going to be the same as the number of female students that like a color (for example purple). Then if for each color the value is not between the confidence interval, we can surely say that the color depends on the gender. Im not sure, im just a molecular bio student
As often observed calculate correctly? Anyone can therefore always help me when I make these calculations (25 * 50) / 200 then it comes 6.25 No. 22 and not the correct serious Opaque (22-6.25) ^ 2 where's questions do not know how to reach this values! Thank you! YES NO TOTAL YES ....... 6.25 + (? -43.75) ^ 2 / 43, 75 + (? -18.75) ^ 2 / 18, 75 + (? -131.25) ^ 2 / 131, 25 =
thank you but I have a question in this why the null hypothesis is taken that there is no relationship ? in others we null hypotheses is always taken as equal and alternative as unequal
H0 States that the observed data should equal the expected data. What this means is dependant on what is being tested. In Chi square test for goodness of fit, the null states that there is no *difference* between the observed and expected values, while in the Chi square for independance, the null states there is no *relationship* between two variables, in this case gender and colour. If there is no relationship between gender and favourite colour, then the data observed would equal the expected data.
Apologies if this is completely useless for you now. At the very least this good revision for me to see if I understand the base concepts of what is going on.
Before teaching statistics he should learn basic calculations. Sum of rows (boys and girls) are not correct. For the data given in the table, the Chi-Square value is 259.796
there is an error in the sum of boys and girls 270 instead of 300 and 230 instead of 200 wich changes the results
Hello I just wanted to comment that your videos has helped me understand business statistics better and made me love learning it. As I religiously watch your videos before every business statistics lessons I have, I get very excited to learn and I haven't felt that about studying in so long and I'm really glad your videos helped me gain that back. I want to thank you for the examples and explanations and for helping me get straight As 😂. I've never felt so accomplished in my life before and it's my proudest achievement. Thank you. 😊
I have watched a number of videos on You Tube for Chi Squared and I have to say this is the best one I have seen.
very true
clear and easy explanation. Only mistake was the total of the rows but it one can figure it out. Good video!
Your row totals are incorrect
For anyone who's curious the correct row totals are 270 for boys and 230 for girls. After similar calculations to those in his video, the chi-squared value is 259.796. So you still reject the null hypothesis.
@@Scrappy527 Thank you!
@@Scrappy527 Im getting the same answer 259.796 (thumbs up)
(2)
@@Scrappy527thankyou so much!
@DonZaka93 The problem is wrong, the way he works on it is right but the mistake was when he added the totals of the observed values, he set 300 and 200, when in reality the totals are 270 and 230 (therefore screwing up the calculation of expected values, and result of x2)
Are you still alive?
this video is a life-saver. thank you
You are the best sir I have watched many videos but your own is the best,brief and well explained 👋🏻
If you could fix the computational errors in this video it would be great. To find your expected values, divide by 500 (not 72).
the row totals are incorrect .. this is true.. but thank you for simplifying this
This video confused me so badly. I had no idea where his 276.389 value had come from T^T.. Thank god for the comments saying that the correct x^2 = 259.796 because that is what showed up on my calculator :)
Can we use Chi-squared when we have more than 2 classifications such as Male Females and Trans?
So the degrees of freedom will be
(3-1)*(3-1) = 4
Is that right?
Thanks a lot dear. Regardless of the minor calculation error, your explanation is REALLY great and that is what I need. THANKS A MILLION
Honestly, i dont get how my statistics Professors could make something so seemingly easy that complicated. I mean, ive learned more in 4 minutes here than in 20 minutes in university
I always supplement what I learn in university with videos like these. Its always good to get multiple perspectives of a concept, which greatly helps you understand it better.
thank you so much for your videos. I am confident that I can pass my stat subject because of your very helpful videos. Clear, brief and concise.
there is a little problem in the first cart.
100+150+20 is not equal 300
your row totals are wrong
I think you have the error right there at the marginal frequencies (total area). How come for the boys, 100 + 150 + 20 = 300? It is very wrong!!!!
ikr?!
was bothering me so much
Is this a two tailed test or one-tailed test. If two-tailed there will be two critical values right.
shouldn't H0 and H1 be reverse? because in H0 we say there is no significant difference b/w 2 groups
quick and clear explanation! thanks a lot!
are those role totals correct ?
Thank you so much, I know that there is a mistake in the marginal frequencies but it does not interfere in the way you explain it. It is very helpful!
Thanks
Hi, quick question, why you used that Null Hypothesis as not related (gender and favorite color) when mostly in statistics the Null hypothesis for equal, and alternative for not equal, more or less?
you mean, that the observed value is similar to the expected value? Because i can't see how you could relate the chi-square test to this problem. I would use the double sample t-test. We are expecting that the number of male students is going to be the same as the number of female students that like a color (for example purple). Then if for each color the value is not between the confidence interval, we can surely say that the color depends on the gender. Im not sure, im just a molecular bio student
Thank you, the formulas helped me reach the same solution as my STATS memo...
Why do we say that null hypothesis "gender and color not related". How do I know what null hypothesis should state?
Who came here after watching KRISH NAIK sir lectures..
HI can we use chi square to determine relationship in likert questions?
HOW TO DECIDE NULL AND ALTERNATIVE HYPOTHESES???
why row total is 300 instead of 270? Totally screw up answer you have.
It's really helpful (y)
Thank you so much sir ❤️
thank you so much
As often observed calculate correctly?
Anyone can therefore always help me when I make these calculations (25 * 50) / 200 then it comes
6.25 No. 22 and not the correct serious Opaque (22-6.25) ^ 2
where's questions do not know how to reach this values!
Thank you!
YES NO TOTAL
YES ....... 6.25 + (? -43.75) ^ 2 / 43, 75 + (? -18.75) ^ 2 / 18, 75 + (? -131.25) ^ 2 / 131, 25 =
Any data scientist is here from 2023 ?
i just wish this was explained for in SPSS
wrong answer,,, there is an error in sum of rows
Best Explaination ever
sum of rows is not accurate....
thanks
come at 2024 to watch this
How would this work if you only have one column (yes/no using reusable cups) and two rows (gender male/female)?
Thanks. Now I can sleep. 😊
Hi, I'm still curious, How if we change the parameter H0 to become the favourite colour are preferred to the gender. Is that also changing the result?
This is so much simpler to understand compared to my lecturer's notes. My saviourrrr😭
Aslam o alaikum respected sir very nice and informative vedio
thank you but I have a question in this why the null hypothesis is taken that there is no relationship ? in others we null hypotheses is always taken as equal and alternative as unequal
thank you!!!
I have watched the video over and over again, and this is very clear and informative as well as educational
I have to say your videos are really useful but for this one. shouldn't hypothesis null always be equal? so the gender and color are related?
H0 States that the observed data should equal the expected data. What this means is dependant on what is being tested. In Chi square test for goodness of fit, the null states that there is no *difference* between the observed and expected values, while in the Chi square for independance, the null states there is no *relationship* between two variables, in this case gender and colour. If there is no relationship between gender and favourite colour, then the data observed would equal the expected data.
Apologies if this is completely useless for you now. At the very least this good revision for me to see if I understand the base concepts of what is going on.
10/10
Thank you! You explained it better than my prof. Watched this 10 minutes before my final (:
Coketa hows your result? 😂😂
@DonZaka93 i got in my calculaor 276.3888889 you guys are missing something
THANK YOU SO MUCH!!!!!
Thanks for clearing my concept
and how do you know alpha is 0,05 ?
Thank you so much u saved me some precious hours before exam🤲
YAWA LISOD KAAYO
@DonZaka93 may be u r rounding off the decimal values. leave them as they are :)
thaaaaank you
wow..nicely explained...within this short time😍😍😍
You simply made understanding this simple in a sequential step
Thank you
@DonZaka93 I got 259.79 too. Checked it on my TI83.....
thank you very much!
did you just compare the test statistic to alpha to get a conclusion on the hypothesis test?
You compare it to the decision rule you obtained from alpha and the degrees of freedom. Which was 5.99 in this case.
@@TheSniper9752 Yeah, thanks. after rewatching i dont know what i was thinking back then
very clear : ) thanks
Thank you, Jesse Eisenberg
Short. Sweet. And to the point. Well done sir.
Very helpful thank you so much
Thank you 🙏🏼
Thanks 😊☺️👍☺️😊☺️
thank you :)
thanks alot!
amazing!!!!
LUVVV UUU!!
Before teaching statistics he should learn basic calculations. Sum of rows (boys and girls) are not correct. For the data given in the table, the Chi-Square value is 259.796
I got 259.796 as well. That said, don't be a dick, yavuz. It's a great video that really helped me out.
hello there, i just wanted to know, which is the other kind of chi square test apart from this test of independence??
Goodness of fit, and Test of homogeneity.
Goodness of fit test
Could anyone plz explain how the degree of freedom is calculated as In both the videos I saw it quite differently
Thnx... Well Explained ❤❤
wow, this video is so short and concise but very well done.
Helped me a lot man thanks