Standard deviation of a normal data distribution is a . Group of answer choices

measure of data dispersion
measure of data centrality
measure of data quality
measure of data shape

Standard deviation of a normal data distribution is a measure of data dispersion.

Step-by-step explanation:

Standard deviation is used to measure dispersion which is present around the mean data.

The value of standard deviation will never be negative.

The greater the spread, the greater the standard deviation.

Steps-

1. At first, the mean value should be discovered.

2.Then find out the square of it's distance to mean value.

3.Then total the values

4.Then divide the number of data point.

5.the square root have to be taken.

Formula-

SD=

   Advantage-

It is used to measure dispersion when mean is used as measure of central tendency.

there are lots of ways.   pick's theorem tells us if the vertices are lattice points the area a is

a = b/2 + i - 1

where b is the number of boundary lattice points and i is the number of interior lattice points.

in the figure i count b=16, i=50 so

a = 8 + 50 - 1 = 57

let's try the shoelace formula.   the area is half the sum of the cross products of the sides.  

a(-2,6)   -2(2)-6(-5) = 26

b(-5,2)   -5(-3) - 2(-2) = 19

c(-2,-3) -2(-3) - (-3)(4) = 18

d(4,-3)   4(3) - (-3)(5) = 27

e(5,3)   5(3) - 3(1) = 12

f(1,3)     1(6) - 3(-2) = 12

a(-2,6)

each of the cross products is twice the area of the triangle with the associated side and one vertex the origin. so the area of abo=26/2=13.

area = (1/2) (26 + 19 +   18 + 27 + 12 + 12) = 57

that checks!