Can anyone tell me what should be the answer to this question?
What term is being described:
Choose from these answers:
(A)Central Limit Theorem
(B)Normal distribution
(C)Standard Error
(D)Z-score
(E)Transformation rules
1) If you keep taking more and more samples, the average of the samples' Measurement of something will get closer and closer to the true average of the full population's measure of it. ?
2) Convert a raw score into how many standard deviations it is from the mean?
It doesn't take much to figure this one out...
In probability theory, the central limit theorem (CLT) states that, given certain conditions, the arithmetic mean of a sufficiently large number of iterates of independent random variables, each with a well-defined expected value and well-defined variance, will be approximately normally distributed, regardless of the ...
Central limit theorem - Wikipedia, the free encyclopedia
en.wikipedia.org/wiki/Central_limit_theoremWikipedia
Math - Anonymous, Friday, April 24, 2015 at 5:09pm
Whats for the part 2? bobpursley
Math - Damon, Friday, April 24, 2015 at 6:05pm
Z score
Part 1 should be Central Limit Theorem? Ms. Sue
Yes -- That's what bobpursley told you.
Thank You. Ms. Sue
Thank you Bobpursley! :-)
1) The term being described in the first question is the (A) Central Limit Theorem. The Central Limit Theorem states that when independent random variables are added, their normalized sum tends toward a normal distribution, regardless of the shape of the original distribution.
To arrive at this answer, you can analyze the statement and identify the key phrase "average of the samples' Measurement of something will get closer and closer to the true average of the full population's measure of it." This aligns with the concept of the Central Limit Theorem, which deals with the behavior of sample means.
2) The term being described in the second question is the (D) Z-score. A Z-score represents how many standard deviations a raw score is above or below the mean of a distribution.
To determine this answer, you can focus on the phrase "Convert a raw score into how many standard deviations it is from the mean." This concept corresponds to the calculation of a Z-score, which allows you to standardize raw scores within a distribution.