# I need help figuring this out, I got the wrong answers. histogram that displays a grouped data in which every class has the same frequency is described as A. Symmetrical distributionB. Rectangular...

I need help figuring this out, I got the wrong answers.

histogram that displays a grouped data in which every class has the same frequency is described as

A. Symmetrical distribution

B. Rectangular or uiniform distribution

C. Skewed left distribution

D. bimodal distribution

E. Skewed right distribution

How would the dispersion (or variability) of the sampling distribution of sample means compare to the dispersion (or variability) of its corresponding population?

A. The sampling distribution would have more variability

B. The sampling distribution would have less variability

C. The variability would be the same for both

D. The sampling distribution would have no variability

Random samples of size 625 are taken from a normal distribution with a mean 144 and a standard deviation of 30. The standard error of the mean, standard deviation, for the sampling distribution of sampling mean is

A. 12

B. 2.5

C. 1.2

D. 25

The average mortgage is $140,000. Assume that for all homeowners this debt x is normally distrbuted with a standard deviation of $5,000.

Which one of following represents the expression, "The probability that a homeowner owes less than $135,000" ?

A. P(x > 135,000)

B. P (x < 135,000)

C. P (x ≤ 135, 000)

(1) This is an example of uniform distribution. In a way it is symmetrical, but uniform is the best answer. The histogram looks like a rectangle.

(2) The sampling distribution has less variability. The population is spread out more than any sample/group of samples could be.

(3) The standard error of the mean is `s/sqrt(n)` or `sigma/sqrt(n)` :

Here we have `30/sqrt(625)=1.2`

(4) P(x<135000)

P(x>135000) is the probability that a random home owner owes more than 135000.

`P(x<=135000)` is the probability that a random homeowner owes no more than 135000.