2.7-2.5= What does this equal?

Maths!

Ber [7]

Answer:

(1) Variance = 4.5 and Standard deviation = 2.121.

(2) Variance = 4.5 and Standard deviation = 2.121.

(3) The effect on the measure of dispersion if each value is changed uniformly is that it remains unchanged.

Step-by-step explanation:

We are given with the following set of data below;

X $X-\bar X$ $(X-\bar X)^{2}$

5 5 - 8 = -3 9

8 8 - 8 = 0 0

10 10 - 8 = 2 4

9 9 - 8 = 1 1

6 6 - 8 = -2 4

Total 72 36

Firstly, the mean of the above data is given by;

Mean, $\bar X$ = $\frac{\sum X}{n}$

= $\frac{72}{9}$ = 8

(1)Now, the variance of the given data is;

Variance = $\frac{\sum (X-\bar X)^{2} }{n-1}$

= $\frac{36}{9-1}$ = 4.5

So, the standard deviation, (S.D.) = $\sqrt{\text{Variance}}$

= $\sqrt{4.5}$ = 2.12

(2) Now, each value is added by 2; so the new data set is given by;

X $X-\bar X$ $(X-\bar X)^{2}$

7 7 - 10 = -3 9

10 10 - 10 = 0 0

12 12 - 10 = 2 4

11 11 - 10 = 1 1

8 8 - 10 = -2 4

Total 90 36

Firstly, the mean of the above data is given by;

Mean, $\bar X$ = $\frac{\sum X}{n}$

= $\frac{90}{9}$ = 10

(1)Now, the variance of the given data is;

Variance = $\frac{\sum (X-\bar X)^{2} }{n-1}$

= $\frac{36}{9-1}$ = 4.5

So, the new standard deviation, (S.D.) = $\sqrt{\text{Variance}}$

= $\sqrt{4.5}$ = 2.12

(3) The effect on the measure of dispersion if each value is changed uniformly is that it remains unchanged as we see in the case of variance or standard deviation.

4 0

3 years ago

The formula P = 6s gives the formula for the perimeter of a regular hexagon with side length s. What is the perimeter of a regul

stellarik [79]

YOU NEED A BETTER SCHOOL

6 0

3 years ago

Im Desparate! So Very Desparate xD Please Answer All!

notsponge [240]

2 - b.
3 - a.

I'm not sure about 4. Hope this helps!

4 0

3 years ago

In 1982 Abby’s mother scored at the 93rd percentile in the math SAT exam. In 1982 the mean score was 503 and the variance of the

oksian1 [2.3K]

Answer:

The percentle for Abby's score was the 89.62nd percentile.

Step-by-step explanation:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation(which is the square root of the variance) $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Abby's mom score:

93rd percentile in the math SAT exam. In 1982 the mean score was 503 and the variance of the scores was 9604.

93rd percentile. X when Z has a pvalue of 0.93. So X when Z = 1.476.

$\mu = 503, \sigma = \sqrt{9604} = 98$