Difference Between Z-test, F-test, And T-test _ Brandalyzer

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Difference between Z-test, F-test, and T-test

Posted by: bsaikrishna on: December 5, 2010

In: Statistics | Uncategorized 24 Comments

A z-test is used for testing the mean of a population versus a standard, or comparing the means of twopopulations, with large (n 30) samples whether you know the population standard deviation or not. It

is also used for testing the proportion of some characteristic versus a standard proportion, or comparing

the proportions of two populations.Example:Comparing the average engineering salaries of men versus women.

Example: Comparing the fraction defectives from 2 production lines.

A t-test is used for testing the mean of one population against a standard or comparing the means of

two populations if you do not know the populations standard deviation and when you have a limitedsample (n < 30). If you know the populations standard deviation, you may use a z-test.

Example:Measuring the average diameter of shafts from a certain machine when you have a small

sample.

An F-test is used to compare 2 populations variances. The samples can be any size. It is the basis ofANOVA.

Example: Comparing the variability of bolt diameters from two machines.

Matched pair test is used to compare the means before and after something is done to the samples. A t-test is often used because the samples are often small. However, a z-test is used when the samples arelarge. The variable is the difference between the before and after measurements.

Example: The average weight of subjects before and after following a diet for 6 weeks



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Tags: difference, F-test, T-test, Z-test

24 Responses to "Difference between Z-test, F-test, and T-test"

1 | aku

November 16, 2011 at 8:25 pm

thank buddy

Reply

2 | uday

May 17, 2012 at 10:03 am

thank you. this seems a clear description of the question

Reply

3 | TIMOTHY

July 25, 2012 at 12:32 pm

QUITE HELPFUL,THANK YOU!

Reply

4 | Hawa

August 27, 2012 at 4:39 pm

thanks buddy

Reply

5 | company branding Columbus ohio

August 30, 2012 at 8:37 am

Your style is really unique compared to other people Ive read stuff from. Thanks for posting when you

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Your style is really unique compared to other people Ive read stuff from. Thanks for posting when youhave the opportunity, Guess Ill just bookmark this blog.

Reply6 | C kOctober 7, 2012 at 8:05 pm

Good explanation , request you add some more blogs like this , Simple and to the point explanation.

Reply7 | Mai Thanh LuanOctober 9, 2012 at 8:21 am

good explanation. Thank you very much

Reply8 | uschiNovember 28, 2012 at 1:53 pm

very easy and simple to understand. Thank you and keep the good works going on.

Reply9 | toubab95December 10, 2012 at 2:28 pm

at last a good and and clear explanation !!! thanks

Reply10 | karishmaFebruary 20, 2013 at 9:12 am

Hi , thanks for this explanation . It helped , but i still have one doubt. Can Z test be still used for

comparing proportion of two samples when sample size is less than 30 ? for example i need to comparethe conversion rate of two campaigns for 15 days . can i use Z test here ?

Reply11 | kjbkbklbApril 17, 2013 at 8:32 pm

Hello.

When comparing the average engineering salaries of men versus women, why would we use a z-testas opposed to just comparing the averages for men versus women?

Reply

LAWSeptember 28, 2013 at 1:41 pm

Direct comparison of two averages doent account for the variance of the individual data. One group



Direct comparison of two averages doent account for the variance of the individual data. One group

could have a very small distribution of incomes and the other much larger. Then it is possible that theaverage of the small variance group lies within the distribution of the large variance group and that the

difference between the averages isnt actually meaningful.

Reply12 | ravi

May 9, 2013 at 6:36 pm

the information was simple and easy to understand

thank you for your efforts

Reply13 | Emperor Social

May 12, 2013 at 10:45 am

Appreciating the persistence you put into your blog and in depth information you present.Its great to come across a blog every once in a while that isnt the same out

of date rehashed information. Excellent read! Ive bookmarked your site and Im adding your RSSfeeds to my Google account.

Reply

14 | scooter

July 12, 2013 at 4:08 am

OMG why couldnt my professor have just said this. Or maybe he did but I didnt realize it b/c isEnglish is so crappy.

Reply

15 | wudiSeptember 4, 2013 at 2:08 pm

very easy way expressed .thanks

Reply16 | subramaniabharathi

September 12, 2013 at 3:44 pm

thank you very much,dear/

Reply17 | The Maddening Transience of Memory | Chasing Hollyfeld

October 19, 2013 at 9:36 pm

[] in statistics in my life, and almost every time I do one, I have to go double-check to make sure

which is which; about half the time, Im wrong. I just dont do them often enough that the information[]



Reply18 | gccheng

October 30, 2013 at 6:42 pm

Reblogged this on GUANGCHUN CHENG.

Reply19 | Vanlalrema Kuki

November 28, 2013 at 8:51 am

clear and basic

Reply

20 | kristinFebruary 27, 2014 at 7:14 am

Even tha slow learners easily understand this. Thenks n keep it up

Reply

21 | Seth StephenApril 25, 2014 at 2:03 am

very xlear and easy to understand , not that complicated as other information i read. thanks alot

very easy and reliable explanation it helped me much ,thanks alot

Reply

22 | Suoton EkineJuly 19, 2014 at 6:11 pm

I thank you very much for this work. I must confess the work is nice.

Reply

23 | shaina vermaAugust 23, 2014 at 9:39 am

thsnk u so much . the concept is to be to me know

Reply

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Difference Between Z-test, F-test, And T-test _ Brandalyzer

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