What if we choose a sample from the right side of the distribution? In that case, we will have to reduce the sample variance and have to use (n+1) in the denominator. Isn't it?
I am also wondering the same but conclusion that i am drawing from this concept is that I think it was like if we choose any sample from a population example for measuring variance in weight of 500 cans i am taking 5 can sample let it be 25.1 g ,25.2g,25.2g,25.3g,25.4g.so while calculating variance with n=5 i will get some sought of low value of variance in my sample, so to improve uniformity of that value for whole population we take value of n-1.it is irrespective of from where you were choosing your sample coz if you will choose from right side of population mean all the 5 values of weight will be greater than left side values but when you calculate variance with n-1 for those sample you will get same results. what you are focusing on is that how weight variance is there within your sample space and we can take some step(like replacing n with n-1 ) for estimating it for whole population . this result has came out of various research . you can take any problem try for both sides with n-1 you will get approximately same results.
@5MinutesEngineering Sir I have a doubt I clearly agree to what you explained in the video here you took the case when our sample data is far away from population data but what if in some case our sample mean lies very near to the population mean, then difference between them will be very less.
Statistics key sarey formula ka ek jagah likhwa do super advance level par kaam hoga to naturally universe is pata chal jayega ki kitna naturally universe ki efficiency hain maximum
why do he compared sample variance with the population mean not with the population variance at 3:41 ,how do some visuallize population variance in plot diagram
The Population Variance and Sample Variance are the params that we are LOOKING for. This is in reference to the Population/ Sample at hand. He is trying to explain WHY we use Only 'n-1' in denominator for sample variance when we use 'n' for the population. Hence, the comparison. For the basic understanding of the formula you need to see the last video that explains the concept of Variance.
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thank you. you teach so nicely within 5 minutes. love your way of teachning. god bless you.
for this free service you are doing to society
You are great sir!
I see a problem here... If sample data is on right side of the mean then n-1 will take it more far than mean
thanku so mch sir, this is very much imp concept for me to understand & u explained it very well
What if we choose a sample from the right side of the distribution? In that case, we will have to reduce the sample variance and have to use (n+1) in the denominator. Isn't it?
I am also wondering the same but conclusion that i am drawing from this concept is that I think it was like if we choose any sample from a population example for measuring variance in weight of 500 cans i am taking 5 can sample let it be 25.1 g ,25.2g,25.2g,25.3g,25.4g.so while calculating variance with n=5 i will get some sought of low value of variance in my sample, so to improve uniformity of that value for whole population we take value of n-1.it is irrespective of from where you were choosing your sample coz if you will choose from right side of population mean all the 5 values of weight will be greater than left side values but when you calculate variance with n-1 for those sample you will get same results.
what you are focusing on is that how weight variance is there within your sample space and we can take some step(like replacing n with n-1 ) for estimating it for whole population . this result has came out of various research . you can take any problem try for both sides with n-1 you will get approximately same results.
although exact reason nobody knows
The thing is anyway you are squaring to remove negative and positive
Bohut achchese samajh mein aa gayi😁thank you sir😊
All I can say is thank you thank you ...!
Amazing video, your teaching style the way you make topics so simple is mind-blowing! Binged watched your whole Blockchain playlist.
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😂
A lot of clarity was there in your video..thanks sir🤍
thanks bhai...
@5MinutesEngineering Sir I have a doubt I clearly agree to what you explained in the video here you took the case when our sample data is far away from population data but what if in some case our sample mean lies very near to the population mean, then difference between them will be very less.
you are doing great keep doing
Amazing video
Thank you so much sir
then why only n-1 not n-2 or n-3 ?? Can you explain with using little mathmatical evidences?
No, Have a doubt if our sample is on the extreme right side than if we calculate using n-1 , it will go more far from the actual population mean.
Luv u I search for it
Sir aap muze 3 sal pahale mile hote to meri jindagi badal jati, muze reaserch methodology kabhi samazi nahi, lekin lag raha hai ab samjegi
or sir agr humne esa sample le liya jiska variance population se bada hai to (n-1) bad o to or bada ho jayega?
thank you
Statistics key sarey formula ka ek jagah likhwa do super advance level par kaam hoga to naturally universe is pata chal jayega ki kitna naturally universe ki efficiency hain maximum
Great teaching
Statistics key sarey formula ka ek function banva do jo kisi bhi database ko reserch karwavo phir Duniya following karegi
why do he compared sample variance with the population mean not with the population variance at 3:41 ,how do some visuallize population variance in plot diagram
The Population Variance and Sample Variance are the params that we are LOOKING for. This is in reference to the Population/ Sample at hand. He is trying to explain WHY we use Only 'n-1' in denominator for sample variance when we use 'n' for the population. Hence, the comparison. For the basic understanding of the formula you need to see the last video that explains the concept of Variance.
i gave a like
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Thank you so much sir