Answer:
[tex]Mean = 48.6364[/tex]
[tex]s^2 = 331.8545[/tex] -- Sample Variance
[tex]s = 18.2169[/tex] --- Sample Standard Deviation
Step-by-step explanation:
Given
[tex]n = 11[/tex]
[tex]Data: 24, 41 ,25 ,68 ,53 ,83 ,43 ,63 ,56 ,34 ,45[/tex]
Solving (a): The sample mean
[tex]Mean = \frac{\sum x}{n}[/tex]
So:
[tex]Mean = \frac{24 +41 +25 +68 +53 +83 +43 +63 +56 +34+ 45}{11}[/tex]
[tex]Mean = \frac{535}{11}[/tex]
[tex]Mean = 48.6364[/tex]
Solving (b): Sample variance (s^2)
This is calculated as:
[tex]s^2 = \frac{\sum (x - \bar x_i)^2}{n - 1}[/tex]
Where:
[tex]\bar x = 48.6364[/tex]
So:
[tex]s^2 = \frac{(24 -48.6364)^2 +(41 -48.6364)^2 +......................+( 45 -48.6364)^2}{11-1}[/tex]
[tex]s^2 = \frac{3318.54545456}{10}[/tex]
[tex]s^2 = 331.8545[/tex]
Solving (c): Sample Standard Deviation (s)
This is calculated as:
[tex]s = \sqrt {s^2[/tex]
[tex]s = \sqrt{331.8545[/tex]
[tex]s = 18.2169[/tex]