The formula for the standard deviation (S.D) of a set of values is:
\[
S.D = \sqrt{\frac{1}{N} \sum_{i=1}^{N} (x_i - \mu)^2}
\]
Where:
- \( N \) is the number of values,
- \( x_i \) are the individual values,
- \( \mu \) is the mean of the values.
### Step 1: Find the Mean (\(\mu\))
The mean is given by the formula:
\[
\mu = \frac{1}{N} \sum_{i=1}^{N} x_i
\]
Substitute the given values:
\[
\mu = \frac{-3 + 0 + 3 + 8}{4} = \frac{8}{4} = 2
\]
### Step 2: Calculate the squared differences from the mean
Now, calculate the squared differences from the mean for each value:
- For \( x_1 = -3 \): \( (-3 - 2)^2 = (-5)^2 = 25 \)
- For \( x_2 = 0 \): \( (0 - 2)^2 = (-2)^2 = 4 \)
- For \( x_3 = 3 \): \( (3 - 2)^2 = (1)^2 = 1 \)
- For \( x_4 = 8 \): \( (8 - 2)^2 = (6)^2 = 36 \)
### Step 3: Calculate the variance
The variance is the average of the squared differences:
\[
\text{Variance} = \frac{25 + 4 + 1 + 36}{4} = \frac{66}{4} = 16.5
\]
### Step 4: Find the Standard Deviation
Finally, take the square root of the variance:
\[
S.D = \sqrt{16.5} \approx
4.06
\]
Thus, the standard deviation is approximately \(
4.06 \).