Answer:
a. 125.0714; 11.1835.
b. 109.4375; 10.4612.
Step-by-step explanation:
Given the following data;
70, 65, 71, 78, 89, 68, 50, 75.
Mean = 70.75
The deviation for the mean of the data is -0.75, -5.75, 0.25,7.25,18.25,-2.75,-20.75, and 4.25.
We would then find the square of this deviation;
[tex]=(-0.75)^2+(-5.75)^2+( 0.25)^2+(7.25)^2 +(18.25)^2+(-2.75)^2+(-20.75)^2 +(4.25)^2[/tex]
[tex]=0.5625+33.0625+0.0625+52.5625+333.0625+7.5625+430.5625+18.0625[/tex]
= 875.5
Next is to find the population variance;
[tex]V = \frac{875.5}{8}[/tex]
Variance, V = 109.4375
The population standard deviation is the square root of the population variance;
[tex]Sd = \sqrt{109.4375}[/tex]
Standard deviation, Sd = 10.4612
To find the sample variance;
[tex]V = \frac{875.5}{8-1}[/tex]
[tex]V = \frac{875.5}{7}[/tex]
Variance, V = 125.0714
The sample variance is;
[tex]Sd = \sqrt{125.0714}[/tex]
Standard deviation, Sd = 11.1835
Therefore,
a. The sample variance is 125.0714 and the sample standard deviation is 11.1835.
b. If this is a population data, the population variance is 109.4375 and the population standard deviation is 10.4612.
