Answer:
a) [tex]\bar X =\frac{67.401+67.400+67.402+67.396+67.406+67.401+67.396+67.401+67.405+67.404}{10}=67.401[/tex]
b) The sample deviation is calculated from the following formula:
[tex]s=\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}[/tex]
And for this case after replace the values and with the sample mean already calculated we got:
[tex] s=0.0036[/tex]
If we assume that the data represent a population then the standard deviation would be given by:
[tex]\sigma=\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n}}[/tex]
And then the deviation would be:
[tex]\sigma =0.00319[/tex]
Step-by-step explanation:
For this case we have the following dataset:
67.401, 67.400, 67.402, 67.396, 67.406, 67.401, 67.396, 67.401, 67.405, and 67.404
Part a: Determine the most probable value.
For this case the most probably value would be the sample mean given by this formula:
[tex] \bar X =\frac{\sum_{i=1}^n X_i}{n}[/tex]
And if we replace we got:
[tex]\bar X =\frac{67.401+67.400+67.402+67.396+67.406+67.401+67.396+67.401+67.405+67.404}{10}=67.401[/tex]
Part b: Determine the standard deviation
The sample deviation is calculated from the following formula:
[tex]s=\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n-1}}[/tex]
And for this case after replace the values and with the sample mean already calculated we got:
[tex] s=0.0036[/tex]
If we assume that the data represent a population then the standard deviation would be given by:
[tex]\sigma=\sqrt{\frac{\sum_{i=1}^n (X_i -\bar X)^2}{n}}[/tex]
And then the deviation would be:
[tex]\sigma =0.00319[/tex]