Answer:
Assuming population data
[tex] \sigma = \sqrt{0.000354}=0.0188[/tex]
Assuming sample data
[tex] s = \sqrt{0.000425}=0.0206[/tex]
Step-by-step explanation:
For this case we have the following data given:
736.352, 736.363, 736.375, 736.324, 736.358, and 736.383.
The first step in order to calculate the standard deviation is calculate the mean.
Assuming population data
[tex]\mu = \frac{\sum_{i=1}^6 X_i}{6}[/tex]
The value for the mean would be:
[tex]\mu = \frac{736.352+736.363+736.375+736.324+736.358+736.383}{6}=736.359[/tex]
And the population variance would be given by:
[tex] \sigma^2 = \frac{\sum_{i=1}^6 (x_i-\bar x)}{6}[/tex]
And we got [tex] \sigma^2 =0.000354[/tex]
And the deviation would be just the square root of the variance:
[tex] \sigma = \sqrt{0.000354}=0.0188[/tex]
Assuming sample data
[tex]\bar X = \frac{\sum_{i=1}^6 X_i}{6}[/tex]
The value for the mean would be:
[tex]\bar X = \frac{736.352+736.363+736.375+736.324+736.358+736.383}{6}=736.359[/tex]
And the population variance would be given by:
[tex] s^2 = \frac{\sum_{i=1}^6 (x_i-\bar x)}{6-1}[/tex]
And we got [tex] s^2 =0.000425[/tex]
And the deviation would be just the square root of the variance:
[tex] s = \sqrt{0.000425}=0.0206[/tex]