Started By
Message

re: "Half the schools are below average" - not always true

Posted on 10/1/14 at 5:17 pm to
Posted by CptBengal
BR Baby
Member since Dec 2007
71661 posts
Posted on 10/1/14 at 5:17 pm to
quote:

Sure I can. We're measuring how many schools fall below average. Look at the OP. Its not that hard to grasp.

You're asserting that for large enough numbers of schools, half will fall below average. You are basing this on the central limit theorem which applies to random samples - however, the samples are not random, meaning you are wrong. (Not surprising from a guy who thinks ice has no mass.)



wow. the stupidity here is on par with runningtiger from the rant.

good luck fatso.
Posted by SpidermanTUba
my house
Member since May 2004
36128 posts
Posted on 10/1/14 at 5:25 pm to
quote:




wow. the stupidity here is on par with runningtiger from the rant.

good luck fatso.



Hey I think I found something you should read
quote:


Central limit theorem (CLT) is considered an important topic in statistics, because it serves as the basis for subsequent learning in other crucial concepts such as hypothesis testing and power analysis. There is an increasing popularity in using dynamic computer software for illustrating CLT. Graphical displays do not necessarily clear up misconceptions related to this theorem. Many interactive computer simulations allow users to explore the programs in a "what-if" manner. However, users may further build up other misconceptions when they start with unclear concepts of the components that contribute to CLT. This paper analyzes common misconceptions in each component of CLT and evaluates the appropriateness of use of computer simulation. CLT states that a sampling distribution, which is the distribution of the means of random samples drawn from a population, becomes closer to normality as the sample size increases, regardless of the shape of the distribution. Misconceptions are found about the following areas: (1) randomness and random sampling; (2) relationships among sample, population, and sampling distribution; (3) normality; (4) parameters of the sampling distribution; and (5) relationships between the sampling distribution and hypothesis testing. (Contains 31 references.) (Author/SLD)
LINK /

Its right up your alley
first pageprev pagePage 1 of 1Next pagelast page
refresh

Back to top
logoFollow TigerDroppings for LSU Football News
Follow us on Twitter, Facebook and Instagram to get the latest updates on LSU Football and Recruiting.

FacebookTwitterInstagram