Statistics Examples

\begin{matrix} Class & Frequency 2 - 10 & 1 11 - 19 & 3 20 - 28 & 9 \end{matrix}

$\begin{array}{c} Class & Frequency \\ 2 - 10 & 1 \\ 11 - 19 & 3 \\ 20 - 28 & 9 \end{array}$

Step 1

Find the midpoint

M

$M$ for each group.

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Step 1.1

The lower limit for every class is the smallest value in that class. On the other hand, the upper limit for every class is the greatest value in that class.

\begin{matrix} Class & Frequency (f) & Lower Limits & Upper Limits 2 - 10 & 1 & 2 & 10 11 - 19 & 3 & 11 & 19 20 - 28 & 9 & 20 & 28 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Lower Limits & Upper Limits \\ 2 - 10 & 1 & 2 & 10 \\ 11 - 19 & 3 & 11 & 19 \\ 20 - 28 & 9 & 20 & 28 \end{array}$

Step 1.2

The class midpoint is the lower class limit plus the upper class limit divided by

2

$2$ .

\begin{matrix} Class & Frequency (f) & Lower Limits & Upper Limits & Midpoint (M) 2 - 10 & 1 & 2 & 10 & \frac{2 + 10}{2} 11 - 19 & 3 & 11 & 19 & \frac{11 + 19}{2} 20 - 28 & 9 & 20 & 28 & \frac{20 + 28}{2} \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Lower Limits & Upper Limits & Midpoint (M) \\ 2 - 10 & 1 & 2 & 10 & \frac{2 + 10}{2} \\ 11 - 19 & 3 & 11 & 19 & \frac{11 + 19}{2} \\ 20 - 28 & 9 & 20 & 28 & \frac{20 + 28}{2} \end{array}$

Step 1.3

Simplify all the midpoint column.

\begin{matrix} Class & Frequency (f) & Lower Limits & Upper Limits & Midpoint (M) 2 - 10 & 1 & 2 & 10 & 6 11 - 19 & 3 & 11 & 19 & 15 20 - 28 & 9 & 20 & 28 & 24 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Lower Limits & Upper Limits & Midpoint (M) \\ 2 - 10 & 1 & 2 & 10 & 6 \\ 11 - 19 & 3 & 11 & 19 & 15 \\ 20 - 28 & 9 & 20 & 28 & 24 \end{array}$

Step 1.4

Add the midpoints column to the original table.

\begin{matrix} Class & Frequency (f) & Midpoint (M) 2 - 10 & 1 & 6 11 - 19 & 3 & 15 20 - 28 & 9 & 24 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) \\ 2 - 10 & 1 & 6 \\ 11 - 19 & 3 & 15 \\ 20 - 28 & 9 & 24 \end{array}$

\begin{matrix} Class & Frequency (f) & Midpoint (M) 2 - 10 & 1 & 6 11 - 19 & 3 & 15 20 - 28 & 9 & 24 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) \\ 2 - 10 & 1 & 6 \\ 11 - 19 & 3 & 15 \\ 20 - 28 & 9 & 24 \end{array}$

Step 2

Calculate the square of each group midpoint

M^{2}

$M^{2}$ .

\begin{matrix} Class & Frequency (f) & Midpoint (M) & M^{2} 2 - 10 & 1 & 6 & 6^{2} 11 - 19 & 3 & 15 & 15^{2} 20 - 28 & 9 & 24 & 24^{2} \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & M^{2} \\ 2 - 10 & 1 & 6 & 6^{2} \\ 11 - 19 & 3 & 15 & 15^{2} \\ 20 - 28 & 9 & 24 & 24^{2} \end{array}$

Step 3

Simplify the

M^{2}

$M^{2}$ column.

\begin{matrix} Class & Frequency (f) & Midpoint (M) & M^{2} 2 - 10 & 1 & 6 & 36 11 - 19 & 3 & 15 & 225 20 - 28 & 9 & 24 & 576 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & M^{2} \\ 2 - 10 & 1 & 6 & 36 \\ 11 - 19 & 3 & 15 & 225 \\ 20 - 28 & 9 & 24 & 576 \end{array}$

Step 4

Multiply each midpoint squared by its frequency

f

$f$ .

\begin{matrix} Class & Frequency (f) & Midpoint (M) & M^{2} & f \cdot M^{2} 2 - 10 & 1 & 6 & 36 & 1 \cdot 36 11 - 19 & 3 & 15 & 225 & 3 \cdot 225 20 - 28 & 9 & 24 & 576 & 9 \cdot 576 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & M^{2} & f \cdot M^{2} \\ 2 - 10 & 1 & 6 & 36 & 1 \cdot 36 \\ 11 - 19 & 3 & 15 & 225 & 3 \cdot 225 \\ 20 - 28 & 9 & 24 & 576 & 9 \cdot 576 \end{array}$

Step 5

Simplify the

f \cdot M^{2}

$f \cdot M^{2}$ column.

\begin{matrix} Class & Frequency (f) & Midpoint (M) & M^{2} & f \cdot M^{2} 2 - 10 & 1 & 6 & 36 & 36 11 - 19 & 3 & 15 & 225 & 675 20 - 28 & 9 & 24 & 576 & 5184 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & M^{2} & f \cdot M^{2} \\ 2 - 10 & 1 & 6 & 36 & 36 \\ 11 - 19 & 3 & 15 & 225 & 675 \\ 20 - 28 & 9 & 24 & 576 & 5184 \end{array}$

Step 6

Find the sum of all frequencies. In this case, the sum of all frequencies is

n = 1, 3, 9 = 13

$n = 1, 3, 9 = 13$ .

\sum f = n = 13

$\sum_{}^{} f = n = 13$

Step 7

Find the sum of

f \cdot M^{2}

$f \cdot M^{2}$ column. In this case,

36 + 675 + 5184 = 5895

$36 + 675 + 5184 = 5895$ .

\sum f \cdot M^{2} = 5895

$\sum_{}^{} f \cdot M^{2} = 5895$

Step 8

Find the mean

μ

$μ$ .

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Step 8.1

Find the midpoint

M

$M$ for each class.

\begin{matrix} Class & Frequency (f) & Midpoint (M) 2 - 10 & 1 & 6 11 - 19 & 3 & 15 20 - 28 & 9 & 24 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) \\ 2 - 10 & 1 & 6 \\ 11 - 19 & 3 & 15 \\ 20 - 28 & 9 & 24 \end{array}$

Step 8.2

Multiply the frequency of each class by the class midpoint.

\begin{matrix} Class & Frequency (f) & Midpoint (M) & f \cdot M 2 - 10 & 1 & 6 & 1 \cdot 6 11 - 19 & 3 & 15 & 3 \cdot 15 20 - 28 & 9 & 24 & 9 \cdot 24 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & f \cdot M \\ 2 - 10 & 1 & 6 & 1 \cdot 6 \\ 11 - 19 & 3 & 15 & 3 \cdot 15 \\ 20 - 28 & 9 & 24 & 9 \cdot 24 \end{array}$

Step 8.3

Simplify the

f \cdot M

$f \cdot M$ column.

\begin{matrix} Class & Frequency (f) & Midpoint (M) & f \cdot M 2 - 10 & 1 & 6 & 6 11 - 19 & 3 & 15 & 45 20 - 28 & 9 & 24 & 216 \end{matrix}

$\begin{array}{c} Class & Frequency (f) & Midpoint (M) & f \cdot M \\ 2 - 10 & 1 & 6 & 6 \\ 11 - 19 & 3 & 15 & 45 \\ 20 - 28 & 9 & 24 & 216 \end{array}$

Step 8.4

Add the values in the

f \cdot M

$f \cdot M$ column.

6 + 45 + 216 = 267

$6 + 45 + 216 = 267$

Step 8.5

Add the values in the frequency column.

n = 1 + 3 + 9 = 13

$n = 1 + 3 + 9 = 13$

Step 8.6

The mean (mu) is the sum of

f \cdot M

$f \cdot M$ divided by

n

$n$ , which is the sum of frequencies.

μ = \frac{\sum f \cdot M}{\sum f}

$μ = \frac{\sum_{}^{} f \cdot M}{\sum_{}^{} f}$

Step 8.7

The mean is the sum of the product of the midpoints and frequencies divided by the total of frequencies.

μ = \frac{267}{13}

$μ = \frac{267}{13}$

Step 8.8

Simplify the right side of

μ = \frac{267}{13}

$μ = \frac{267}{13}$ .

20.53846153

$20.53846153$

20.53846153

$20.53846153$

Step 9

The equation for the standard deviation is

S^{2} = \frac{\sum f \cdot M^{2} - n {(μ)}^{2}}{n - 1}

$S^{2} = \frac{\sum_{}^{} f \cdot M^{2} - n {(μ)}^{2}}{n - 1}$ .

S^{2} = \frac{\sum f \cdot M^{2} - n {(μ)}^{2}}{n - 1}

$S^{2} = \frac{\sum_{}^{} f \cdot M^{2} - n {(μ)}^{2}}{n - 1}$

Step 10

Substitute the calculated values into

S^{2} = \frac{\sum f \cdot M^{2} - n {(μ)}^{2}}{n - 1}

$S^{2} = \frac{\sum_{}^{} f \cdot M^{2} - n {(μ)}^{2}}{n - 1}$ .

S^{2} = \frac{5895 - 13 {(20.53846153)}^{2}}{13 - 1}

$S^{2} = \frac{5895 - 13 {(20.53846153)}^{2}}{13 - 1}$

Step 11

Simplify the right side of

S^{2} = \frac{5895 - 13 {(20.53846153)}^{2}}{13 - 1}

$S^{2} = \frac{5895 - 13 {(20.53846153)}^{2}}{13 - 1}$ to get the variance

S^{2} = 34.26923076

$S^{2} = 34.26923076$ .

34.26923076

$34.26923076$

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