For the leaves problem, t-value(0.05 significance level,2 tail test, independent type)=0.803, t-critical value(dof=40,0.05 significance level, 2 tail test)=2.021. Since the (t-value < t-critical value), we fail to reject the Null hypothesis(Leaves in both the plant have the same parameter for which it is tested). Hence, there is no significant difference between the leaves of two plants
Absolutely excellent amazing & clear video. Gave amazing clarity on the concept and use and significance of t test. Im awaiting more such videos regarding statistics and research be uploaded soon. Thank you so much sir. 😊
Really nice video, thank you! What a shame you do not explain how to get in excel step by step from the t-value to the p-value., which is the result in the automated excel function.
We accept the null hypothesis, the t-test is 0.838 which is >0.05, hence the difference is not statistically significant! anyone else got the same result?
Straight forward as always. However, I am kind of confused about the 5:58 explanation. if p=0.05 then 95% rejection rate. Then if p=0.025 then 97.5% rejection rate. In this case when t=2.3, it failed the criterial for 95% rejection but met the criterial for 97.5% rejection. How come? I guess there is a miscommunication. P-value actually means that "the chance for such extreme data to show up when the null hypothesis is true" (Wikipedia). The higher it is (the smaller the calculated t-value is), the likely it is to "not reject" the null hypothesis because your data is likely to be normal under null hypothesis. Not sure if it makes it clear :)
At 5:45 you say that if have a p-value of 0.05, this means if we did the experiment 100 times, 95 of the times we would reject the null hypothesis. I don't feel like this is right. Wouldn't we FAIL to reject the null hypothesis 95 of the times? A p-value of 0.05 states that we would expect a result to be as extreme or more extreme 5% of the time. If a p-value is smaller than our significance level then we reject the null hypothesis. It seems like you are saying the opposite here but I'm probably missing something?
minute 2: not number of samples but sample sizes! And "minute 6: why keep doing things at the 5% level of significance when you have the p-value approach?
I still don't completely understand how we come to the conclusion of rejecting the null hypothesis at 7:56. If the new p-value is super close to p = 0.025 which has critical value of 2.36, and our t-value is 2.3, shouldn't we be accepting null hypothesis?
At about 6:07, he explains that he’s using the 0.05 significance level for the calculation. So since the ending p-value is less than 0.05, you would reject the null.
I just started my PhD in Psychology and the program is extremely quantitative. It's been years since I've taken a stats test and watching your videos have seriously helped in me remember the basics. I'm so going to keep you in my prayers! Thank you for making it seem less scary.
Thank you so much Coach Steve Kerr for this lecture video. Despite your busy schedule as the GSW Head Coach, you were still able to find time and record this important topic in Research.
Was that helpful?? God! You have no idea how much I have struggled to wrap my head around this whole Statistics topics. And again, you have no idea what a boon your videos are turning out for me! Many many thanks, Bozeman! You the boss!
Finally! Someone who speaks english! Perfect video showing the real world applications and methodology to come to a conclusion, thank you so much for the entertaining lecture!
I got: t=0.206 t-test(p-value)=0.83814447 Therefore, I fail to reject the null hypothesis, meaning there is no statistical significant difference between the two samples. I had a question though...on the excel spreadsheet do I type in: =ttest(plant A, plant B, 2, 2) or (plant A, plant B, 2, *3* )? The last number is for the "type" and excel reads to put in "3" instead of "2" if the variances are not equal for the two-tailed test. The variances I got seem pretty far apart: *Plant A variance= 138.69 and Plant B variance= 226.29*. Your variances were closer to 1, so I see why you put in "2" for the type. When I put in "3" my p-value turns out to be slightly different= 0.83820433 than 0.83814447. Which is more accurate?
Actually, a variance ratio of 2 isn’t all that uncommon...the t-test is rather robust to unequal variance as I recall, and you probably don’t need to worry until your variance ratio is over 3, in my experience. If you’re in doubt, you can always use the unequal variance option regardless of your variances, since the statistical power of the two methods is pretty much the same. But since the unequal variance option reduces the degrees of freedom compared to the equal variance option, the corresponding critical value for the unequal variance option will be slightly higher., and thus the p-value will be affected as well.
This man needs ALL THE AWARDS. Bruh got me through high school, college, and continues to help me refresh for job relating stuff. This dude is single-handedly responsible for a quarter of millennial contribution to GDP. xD
I believe the explanation in the video is correct. If the t-test gives you a value that is less than the p-value, then you reject the null hypothesis(the difference between the samples is statistically significant). In other words, you compare the p-value with the critical value (0.05 or 0.025), but compare the t-value(the result after putting the numbers in the formula) with the corresponding cell from the distribution table. If the t-value statistic is 'greater' than the corresponding value in the table -> you reject the null hypothesis. If the p-value is 'lesser' than the critical value (0.05 or 0.025) -> you reject the null hypothesis.
Giving you a big like man :) really great explanation .... I learned the T-Test at university but haven't used it for several years so wasn't sure how to count it and you brought it back to my mind ..... really great video man :)
I did the last question about the two plants, I got a t value of 0.21 degrees of freedom is 21+21-2=40 at p=0.05 it is 2.02, therefore the t value of 0.21 is less than critical value of 2.02 therefore we accept the H0 as there is no significant difference is it right? thanks
Hi sir,managed to do the plant example. T-value is 0.205602 & critical value is 2.02. Since t-value is lower than critical value, we don’t reject the null hypothesis right? T-test value is 0.838144. Since p-value is 83.81% than significant value of 5%, therefore we do not reject the null hypothesis again. In other word, there is no statistically significant difference between this plant. Please advise whether my answer is correct?appreciate.
Is it important that one uses correct language--> retain the null or fail to retain the null OR retain the null or reject the null? As one cannot PROVE anything through statistics, we should realize that one can DISPROVE using statistics. As we cannot PROVE our H1/Alternative Hypothesis, we take action on the H0/Null Hypothesis as we can disprove it. Again, we do not PROVE our H1, we only support it all within a probability.
Mr. Andersen, I have had the privilege to meet you in person and tell you, "Thank you!," but it bears repeating here. You have no idea how much you have helped me over the years to understand fundamental concepts that are glossed over in lecture leaving my head spinning unable to follow along. I get home, come to TH-cam and watch you unravel the whole thing in < 15 minutes. You are an exceptionally talented teacher, and your work does not go unnoticed. Thank you for your gift of quality instruction to complete strangers on the internet over many years now. I wish that more teachers would watch your style and emulate that rather than trying to rip through slides or go off on pointless rabbit trails during lecture. "Thank you!"
I got p-value 0.838 for 9:23, the t-value is 0.205602, thus the hypothesis is not rejected, this means that there is no statistically significant difference between Plant A and B Anyone got the same result? Am I correct?
No doubt, the teaching, the content, delivery and everything else was incredible. This is one of the best videos I ever found with complete knowledge. I have just one doubt at 8:35 you mentioned that 0.95 is the probability of rejecting the null hypothesis. But I was unable to grasp it as it always seemed that it is the probability of the acceptance region. Is it different from Z- test? And it will be great if you could make a video on Z test. :)
You are RIGHT! It is the probability of accepting the Null hypothesis. That is how we frame the hypothesis by giving more weightage to Null hypothesis.
This was so helpful! I haven't taken stats in years and have had to partially watch so many videos before finding this one. I really appreciate the clarity and step by step approach!
the link to the excel file does not work. it says 'File not found Sorry, that file doesn’t live here anymore. It might have been moved or made private.'
My values for the end: Critical Value = 2.02 T-value = 0.21 T-test(p) = 0.84 So no statistical significance. I copied the values by hand, so there might be a typo or two, which influenced the results.
Thank you so much, very detailed video, and explained perfectly. I had a biology lab report and I haven't taken a statistics course yet, so I had no clue what to do in Biology X since most kids are older than me !
This video's explanation is excellent! Though I am Japanese, I could not understand T-test, P-value and etc by reading Japanese textbooks of statistics. But now I have understood of them by watching this video. I think, Japanese Professors of all university and college are really bad at explaining in the lectures and of books written by themselves. Thank you a lot!
you are indeed a great teacher. I love this video. I got a t critical which is greater than my t statistics and this establish the claim of the null hypothesis to be true, so I fail to reject the null hypothesis which means that there is no statistical significant difference between the samples. also, my probability value is greater than my alpha value, so this also tells me that my null hypothesis should not be rejected.
I want to see if I am understanding this correctly. We have a t-value of 0.211, p value of 0.838, and df value of 40. Even though the critical value for p=0.05 and df=40 is 2.02, do we say that we don't reject the null hypothesis because it probably won't go below 0.211? Or are we comparing the t-value and p-value directly, which doesn't seem to make much sense to me?
if t stat is less than t critical, you don't reject null hypothesis and vice versa. likewise, you can use p-value and alpha value to make judgment as well. if your pvalue is greater than your alpha value, you must not reject your null hypothesis.
For those of you who don’t quite get the null hypothesis (H0) yet… Essentially, rejecting it means that the data you found is NOT due to random error. Which means that the difference you’re seeing is real and not something that happened by chance.
Fantastic thank you 3:00 t-value formula compares difference in means to difference in variance of the samples. Like a signal to noise ratio. 4:55 once we have a t-value, we can read from the table and see what p-value that t-value corresponds to. That is the t-test, seeing if our t-value is high enough to give us a low p-value (and if so, then the difference in means is statistically significant and we can reject the null hypothesis)
Sir at 7:45 if the answer is between 0.025 and 0.05, it means that the t value should be less than 2.36 as it goes to 2.04. The answer that excel gave us does not fit as you have explained. Please enlighten me on this. thank you!
Dude somehow you don't make me want to die while learning this stuff haha, I wish my professor was more like you, thanks for the help!
Awesome explaination.
fr, my prof is so boring even though he's done some seriously cool engineering work in the past
It had been 7 years and this knowledge still helping me a lot
For the leaves problem, t-value(0.05 significance level,2 tail test, independent type)=0.803, t-critical value(dof=40,0.05 significance level, 2 tail test)=2.021. Since the (t-value < t-critical value), we fail to reject the Null hypothesis(Leaves in both the plant have the same parameter for which it is tested). Hence, there is no significant difference between the leaves of two plants
Finally a video that clearly explained t test. thank you!
Thank you so much! I have to do this for quantitative analysis, and you've made this process so much easier! Again, this video is much appreciated!
Thank you for this excellent and lucid explanation. Best video on statistical applications found so far !
Absolutely excellent amazing & clear video. Gave amazing clarity on the concept and use and significance of t test. Im awaiting more such videos regarding statistics and research be uploaded soon. Thank you so much sir. 😊
You are a genius explaining statistics! ;)
T-value for practice set is 0.205 so we dont reject the hypothesis
Really nice video, thank you! What a shame you do not explain how to get in excel step by step from the t-value to the p-value., which is the result in the automated excel function.
excellent presentation and teaching materials
this his the best explanation I've seen so far.
Very helpful from italian students! Thank you, miao
Great help with my A-Level biology thank you!
We accept the null hypothesis, the t-test is 0.838 which is >0.05, hence the difference is not statistically significant! anyone else got the same result?
You are an amazing teacher, thank you for sharing.
Many thanks for posting such useful videos! May God bless you
This is a great video! Thanks for explaining.
I fail to understand why do we divide variance by n (to calculate t value), since variance itself is a statistic that is averaged over n data items.
why you ignored minus sign in measuring difference of mean in t value calculation?kindly explain its bit confusing
Absolutely Brilliant!
Thank you for this very clear video.
First, thank you for this video, it's amazing. Second, could you please update the excel file link? is no longer working :´(
Thank you very much! Easy and clear!
How would we get t table
thank you so mush for amazing explanation.. just want to ask about the hypothesis table, is it fixed for all kind of samples? and how to get it?
Oh,I will have my final exam,,please bless me
That was amazing, thanks.
Straight forward as always. However, I am kind of confused about the 5:58 explanation. if p=0.05 then 95% rejection rate. Then if p=0.025 then 97.5% rejection rate. In this case when t=2.3, it failed the criterial for 95% rejection but met the criterial for 97.5% rejection. How come? I guess there is a miscommunication.
P-value actually means that "the chance for such extreme data to show up when the null hypothesis is true" (Wikipedia). The higher it is (the smaller the calculated t-value is), the likely it is to "not reject" the null hypothesis because your data is likely to be normal under null hypothesis.
Not sure if it makes it clear :)
BRUH I NOTICED THE SAME THING NOW IM CONFUSED
i tjought we were supposed to base it at .05
At 5:45 you say that if have a p-value of 0.05, this means if we did the experiment 100 times, 95 of the times we would reject the null hypothesis. I don't feel like this is right.
Wouldn't we FAIL to reject the null hypothesis 95 of the times? A p-value of 0.05 states that we would expect a result to be as extreme or more extreme 5% of the time. If a p-value is smaller than our significance level then we reject the null hypothesis. It seems like you are saying the opposite here but I'm probably missing something?
very well explained. thank you
minute 2: not number of samples but sample sizes! And "minute 6: why keep doing things at the 5% level of significance when you have the p-value approach?
I still don't completely understand how we come to the conclusion of rejecting the null hypothesis at 7:56. If the new p-value is super close to p = 0.025 which has critical value of 2.36, and our t-value is 2.3, shouldn't we be accepting null hypothesis?
At about 6:07, he explains that he’s using the 0.05 significance level for the calculation. So since the ending p-value is less than 0.05, you would reject the null.
Thank you!
Thank you sir
why is my t-table different than yours? 30 degrees of freedom a alpha=.05 gives me 1.697
Very helpful
"...so, instead of this being known as the Gosset's t-test, it's known as the -"
*cue smooth electronic beat*
Bozeman really turning science into a tv drama, lol.
he pulled an invincible in 2016
Student T Test
...I still have no clue 😭😭 Probably going to re-watch this a dozen times, cause it explains it better than my lecturer this year
I just started my PhD in Psychology and the program is extremely quantitative. It's been years since I've taken a stats test and watching your videos have seriously helped in me remember the basics. I'm so going to keep you in my prayers! Thank you for making it seem less scary.
How did your PhD go?
@@burtons9922 just finishing. I propose my dissertation on the 27th!
@@zainabmohammed1141 Congratulations!! And good luck next week!
@@zainabmohammed1141 How did the dissertation go?
@@yonisabdull I’m a PhD candidate and defend next month Insha’Allah
Thank you for posting this! You explain statistics far better than most teachers!
i have taken over 10+ stats courses, this was very very well explained
@@NostalgicHearts deez nutz
Completely agree with you. He can explain in one short video what most teachers try to explain in one week's lecture.
0.05 probability means that if we will conduct the experiment 100 times, 95 times we will reject the null hypothesis and 5 times accept....
Why?
Approuved.
What does it meeeaaan? Thanks for the video man
What does that meeEEEeaaAAn?
We calculate the mean but what does that MEAN? (why so mean?)
a comment I anticipated after watching this video haha
literally
mate I was saying the same thing too myself ahah
Thank you so much Coach Steve Kerr for this lecture video. Despite your busy schedule as the GSW Head Coach, you were still able to find time and record this important topic in Research.
ha ha! Love this
Crystal clear description of t- Test. I could finally understand this concept. Thank you !!
you saved my ass, for my exam is tomorrow
Was that helpful??
God! You have no idea how much I have struggled to wrap my head around this whole Statistics topics. And again, you have no idea what a boon your videos are turning out for me! Many many thanks, Bozeman! You the boss!
oh god oh god oh god，A HUGE THANKS FROM CHINA for saving me from my econometrics assignment!
Finally! Someone who speaks english! Perfect video showing the real world applications and methodology to come to a conclusion, thank you so much for the entertaining lecture!
I got:
t=0.206
t-test(p-value)=0.83814447
Therefore, I fail to reject the null hypothesis, meaning there is no statistical significant difference between the two samples.
I had a question though...on the excel spreadsheet do I type in: =ttest(plant A, plant B, 2, 2) or (plant A, plant B, 2, *3* )? The last number is for the "type" and excel reads to put in "3" instead of "2" if the variances are not equal for the two-tailed test. The variances I got seem pretty far apart: *Plant A variance= 138.69 and Plant B variance= 226.29*. Your variances were closer to 1, so I see why you put in "2" for the type. When I put in "3" my p-value turns out to be slightly different= 0.83820433 than 0.83814447. Which is more accurate?
hmm.... Same question here....
I got he same results as you did. I had to type in the 2 in place of the 3
Actually, a variance ratio of 2 isn’t all that uncommon...the t-test is rather robust to unequal variance as I recall, and you probably don’t need to worry until your variance ratio is over 3, in my experience. If you’re in doubt, you can always use the unequal variance option regardless of your variances, since the statistical power of the two methods is pretty much the same. But since the unequal variance option reduces the degrees of freedom compared to the equal variance option, the corresponding critical value for the unequal variance option will be slightly higher., and thus the p-value will be affected as well.
omg... lol I was having trouble with this subject & BAM I get a notification of you uploading this video. THANK YOU.
Double BAM
triple BAM(statQuest)
Watched this during my second undergraduate year, come back as a PhD. student to watch it again :)
Tomorrow is my chemistry exam for which I m watching ur lessons thanks a lot for this understandable video
My problem is I don’t understand WHY we are calculating and what each value means so my brain can’t wrap around the full concept
I actually get it!!! You sir are amazing. I've been reading all this in my textbook and just not getting it. Thank you so much.
The result of t-test is 0.838144 given the alpha level of 0.05, null hypothesis is true.Please let me know if my thought is correct
This man needs ALL THE AWARDS.
Bruh got me through high school, college, and continues to help me refresh for job relating stuff.
This dude is single-handedly responsible for a quarter of millennial contribution to GDP. xD
t-value for practice set =0.205 so we don't reject the null hypothesis; btw, link to file doesn't work
I think its 95% of the time we fail to reject and 5% we would reject since it's based off the null at 5:48
I had the same doubt while watching the video. Did you find the answer to your query?
I believe the explanation in the video is correct. If the t-test gives you a value that is less than the p-value, then you reject the null hypothesis(the difference between the samples is statistically significant). In other words, you compare the p-value with the critical value (0.05 or 0.025), but compare the t-value(the result after putting the numbers in the formula) with the corresponding cell from the distribution table.
If the t-value statistic is 'greater' than the corresponding value in the table -> you reject the null hypothesis.
If the p-value is 'lesser' than the critical value (0.05 or 0.025) -> you reject the null hypothesis.
@@samsung6980 THANK YOU. I HATE STATS SO MUCH
I don't know how but I understand this now.
Hello, I tried clicking the link for the excel file but I couldn't find it anymore
Giving you a big like man :) really great explanation .... I learned the T-Test at university but haven't used it for several years so wasn't sure how to count it and you brought it back to my mind ..... really great video man :)
I did the last question about the two plants, I got a t value of 0.21 degrees of freedom is 21+21-2=40 at p=0.05 it is 2.02, therefore the t value of 0.21 is less than critical value of 2.02 therefore we accept the H0 as there is no significant difference is it right? thanks
Correct, we fail to reject (never accept) the null hypothesis.
Oh my god thank you so much! My biology teachers made zero sense when explaining this!
Excellent example in 10 minutes. Thank you
Hi sir,managed to do the plant example. T-value is 0.205602 & critical value is 2.02. Since t-value is lower than critical value, we don’t reject the null hypothesis right? T-test value is 0.838144. Since p-value is 83.81% than significant value of 5%, therefore we do not reject the null hypothesis again.
In other word, there is no statistically significant difference between this plant. Please advise whether my answer is correct?appreciate.
I’ve learned more in this 10 mins then I have all semester 😩😩 Thank You so much🙏🏾
Is it important that one uses correct language--> retain the null or fail to retain the null OR retain the null or reject the null? As one cannot PROVE anything through statistics, we should realize that one can DISPROVE using statistics. As we cannot PROVE our H1/Alternative Hypothesis, we take action on the H0/Null Hypothesis as we can disprove it. Again, we do not PROVE our H1, we only support it all within a probability.
this is freakazoid clear. thank you. dropbox link is dead tho, so can't run the example.
I wish I somebody showed me this damn video instead going through a readers hundred times and not getting it. Thank you! 🤜
right?!
FINALLY someone uses human language to explain statistics! Thank you!
But what about pooled variance?
Mr. Andersen, I have had the privilege to meet you in person and tell you, "Thank you!," but it bears repeating here.
You have no idea how much you have helped me over the years to understand fundamental concepts that are glossed over in lecture leaving my head spinning unable to follow along. I get home, come to TH-cam and watch you unravel the whole thing in < 15 minutes.
You are an exceptionally talented teacher, and your work does not go unnoticed. Thank you for your gift of quality instruction to complete strangers on the internet over many years now. I wish that more teachers would watch your style and emulate that rather than trying to rip through slides or go off on pointless rabbit trails during lecture. "Thank you!"
Well he probably got noticed now lol
I got p-value 0.838 for 9:23, the t-value is 0.205602, thus the hypothesis is not rejected, this means that there is no statistically significant difference between Plant A and B
Anyone got the same result? Am I correct?
No doubt, the teaching, the content, delivery and everything else was incredible. This is one of the best videos I ever found with complete knowledge. I have just one doubt at 8:35 you mentioned that 0.95 is the probability of rejecting the null hypothesis. But I was unable to grasp it as it always seemed that it is the probability of the acceptance region. Is it different from Z- test? And it will be great if you could make a video on Z test. :)
You are RIGHT! It is the probability of accepting the Null hypothesis. That is how we frame the hypothesis by giving more weightage to Null hypothesis.
My dude!! THANK YOU SO MUCH we really really appreciate your channel! God bless you xx
This was so helpful! I haven't taken stats in years and have had to partially watch so many videos before finding this one. I really appreciate the clarity and step by step approach!
Excellent, but easy explanation
the link to the excel file does not work. it says 'File not found
Sorry, that file doesn’t live here anymore. It might have been moved or made private.'
"use a spreadsheet" oh I wish 😂. Gotta do this in my exam 😂. Thank you.
You have done your test already but if you were allowed to use a calculator than it could have done it for you.
My values for the end:
Critical Value = 2.02
T-value = 0.21
T-test(p) = 0.84
So no statistical significance.
I copied the values by hand, so there might be a typo or two, which influenced the results.
BOZEMAN BACK AT IT AGAIN WITH THE SCIENCE ;)
+Ks Parikh Been traveling for the last few weeks. Feels nice to be home uploading videos again.
+Bozeman Science
people like us always love the science, statistical analysis and other education videos
Thanks Bozeman
هه
اوحه
For between-subject study D.F.=n1+n2-2 but for within-subject study D.F.=n-1.
Thank you so much, very detailed video, and explained perfectly. I had a biology lab report and I haven't taken a statistics course yet, so I had no clue what to do in Biology X since most kids are older than me !
Meaning of 95% confidence level, the meaning that I wanted
This video's explanation is excellent! Though I am Japanese, I could not understand T-test, P-value and etc by reading Japanese textbooks of statistics. But now I have understood of them by watching this video. I think, Japanese Professors of all university and college are really bad at explaining in the lectures and
of books written by themselves. Thank you a lot!
funny my Professor is Japanese
This is my ttest= 0.83 > 0.05 (do not reject). Is my result correct?
you are indeed a great teacher. I love this video. I got a t critical which is greater than my t statistics and this establish the claim of the null hypothesis to be true, so I fail to reject the null hypothesis which means that there is no statistical significant difference between the samples. also, my probability value is greater than my alpha value, so this also tells me that my null hypothesis should not be rejected.
Thank you so much! Please update the link, It's no longer working 💔
I want to see if I am understanding this correctly. We have a t-value of 0.211, p value of 0.838, and df value of 40. Even though the critical value for p=0.05 and df=40 is 2.02, do we say that we don't reject the null hypothesis because it probably won't go below 0.211? Or are we comparing the t-value and p-value directly, which doesn't seem to make much sense to me?
no
we are looking at the value of the t stat and the t critical
if t stat is less than t critical, you don't reject null hypothesis and vice versa. likewise, you can use p-value and alpha value to make judgment as well. if your pvalue is greater than your alpha value, you must not reject your null hypothesis.
the p value and t value both go inverse to each other
thank you sooooo much. these 3 lines by bolaji enabled me to get rid of all doubts.
For those of you who don’t quite get the null hypothesis (H0) yet… Essentially, rejecting it means that the data you found is NOT due to random error. Which means that the difference you’re seeing is real and not something that happened by chance.
This is the best way of introducing Student T-Test I have ever seen! Every easy to understand! Thanks!
This was incredibly helpful! Thank you so much for this amazing lesson!
I would like to know about ANOVA
me too
Fantastic thank you
3:00 t-value formula compares difference in means to difference in variance of the samples. Like a signal to noise ratio.
4:55 once we have a t-value, we can read from the table and see what p-value that t-value corresponds to. That is the t-test, seeing if our t-value is high enough to give us a low p-value (and if so, then the difference in means is statistically significant and we can reject the null hypothesis)
I injected mariweed and I dieded
Which one of your joints had a higher average high?
Thanks Mr. Bozeman! You really helped me out! I have actually been studying this and I could never understand it.
I think we use different formula for DF of unequal variance, n1+n2 -2 is only for equal variance two samples
Yes I had the same question. Like why did we use this formula instead of n-1 for df.
I found this video too late. I have just passed my STAT class. This video would have helped.
What does that meeeean?
Sir at 7:45 if the answer is between 0.025 and 0.05, it means that the t value should be less than 2.36 as it goes to 2.04. The answer that excel gave us does not fit as you have explained. Please enlighten me on this. thank you!
It looks like the t-test formula on excel returns the p value, and not the t-value.
GOD BLESS YOU