Answer:
[tex]\bar x = 13.739[/tex]
[tex]\sigma^2 = 4.923[/tex]
Step-by-step explanation:
Given
[tex]\begin{array}{cc}{Class} & {Frequency} & 10.01 - 11.50 & 44 & 11.51 - 13.00 & 27 & 13.01 - 14.50 & 38 & 14.51 - 16.00 & 33 & 16.01 - 17.50 & 40 \ \end{array}[/tex]
Required
The sample mean and the sample variance
First, calculate the midpoints
[tex]x_1 = \frac{10.01 + 11.50}{2} = 10.755[/tex]
[tex]x_2 = \frac{11.51 + 13.00}{2} = 12.255[/tex]
And so on...
So, the table becomes:
[tex]\begin{array}{ccc}{Class} & {Frequency} & {x} & 10.01 - 11.50 & 44 & 10.755 & 11.51 - 13.00 & 27 & 12.255 & 13.01 - 14.50 & 38 & 13.755 & 14.51 - 16.00 & 33 & 15.255 & 16.01 - 17.50 & 40 & 16.755 \ \end{array}[/tex]
So, the sample mean is:
[tex]\bar x = \frac{\sum fx}{\sum f}[/tex]
[tex]\bar x = \frac{44 * 10.755 + 27 * 12.255 + 38 * 13.755 + 33 * 15.255 + 40 * 16.755}{44 + 27 + 38 + 33 + 40}[/tex]
[tex]\bar x = \frac{2500.41}{182}[/tex]
[tex]\bar x = 13.739[/tex]
The sample variance is:
[tex]\sigma^2 = \frac{\sum f(x - \bar x)^2}{\sum f - 1}[/tex]
[tex]\sigma^2 = \frac{44 * (10.755 - 13.739)^2 + 27 * (12.255 - 13.739)^2+ 38 * (13.755 - 13.739)^2 + 33 * (15.255 - 13.739)^2+ 40 * (16.755- 13.739)^2}{44 + 27 + 38 + 33 + 40-1}[/tex]
[tex]\sigma^2 = \frac{890.950592}{181}[/tex]
[tex]\sigma^2 = 4.923[/tex]