Consider a large population with a mean of 150 and a standard deviation of 27. A random sample of size 36 is taken from this population. The standard error of the sampling distribution of sample mean; SE(X) = σx = q V ar(X) is equal to:

SE(X) = σx = 4.5

Var(X) = 20.25

Step-by-step explanation:

Solution:-

- A large population has a mean ( u ) and standard deviation ( σ ). The parameters of the population distribution are given as follows

                        u = 150

                        σ = 27

- A sample of n = 36 people were taken from the population.

- We will first estimate the sample standard deviation (σ) by assuming that the population is normally distributed with conditions :

                      n  ≥ 30

                      u ≥ 10

- The condition of normality are valid. The population is assumed to be normally distributed. The sample must also be normally distributed. The sample standard deviation (σx):

                       σx = σ/√n  = 27/√36

                       σx = 4.5 ... sample standard deviation.          

- The sample variance can be determined by:

                      Var ( X ) = ( σx ) ^2

                      Var ( X ) = ( 4.5 ) ^2

                      Var ( X ) = 20.25

the answer is a

step-by-step explanation:

18

step-by-step explanation:

draw the shape and you will see that f and k are actually at adjacent vertices (points of the hexagon that are neighboring).   so find the distance between (1,2) and (4,2).   that is easy since (1,2) and (4,2) is just a vertical distance to count, which is 3.   it is a regular polygon which means all sides are congruent.   you have 6 sides (hexa) so multiply 6 by 3 to receive 18.