Let's solve the problem step-by-step.
### Step 1: Calculate the mean of the data
Given data: [tex]\(2400, 1750, 1900, 2500, 2250, 2100\)[/tex]
The mean ([tex]\(\mu\)[/tex]) of the data is calculated as:
[tex]\[
\mu = \frac{2400 + 1750 + 1900 + 2500 + 2250 + 2100}{6} = 2150
\][/tex]
### Step 2: Calculate the squared deviations from the mean
For each value, we subtract the mean and then square the result:
[tex]\[
(2400 - 2150)^2 = 250^2 = 62500
\][/tex]
[tex]\[
(1750 - 2150)^2 = (-400)^2 = 160000
\][/tex]
[tex]\[
(1900 - 2150)^2 = (-250)^2 = 62500
\][/tex]
[tex]\[
(2500 - 2150)^2 = 350^2 = 122500
\][/tex]
[tex]\[
(2250 - 2150)^2 = 100^2 = 10000
\][/tex]
[tex]\[
(2100 - 2150)^2 = (-50)^2 = 2500
\][/tex]
### Step 3: Sum the squared deviations (Numerator of the variance)
[tex]\[
62500 + 160000 + 62500 + 122500 + 10000 + 2500 = 420000
\][/tex]
The numerator in the calculation of variance is thus [tex]\(420000\)[/tex].
### Step 4: Calculate the variance
Variance ([tex]\(\sigma^2\)[/tex]) is the average of these squared deviations:
[tex]\[
\sigma^2 = \frac{420000}{6} = 70000
\][/tex]
### Step 5: Calculate the standard deviation
The standard deviation ([tex]\(\sigma\)[/tex]) is the square root of the variance:
[tex]\[
\sigma = \sqrt{70000} \approx 264.575 \ (\text{rounded to the nearest whole number: } 265)
\][/tex]
### Summary of Results:
Numerator for the calculation of variance: [tex]\(420000\)[/tex]
Variance: [tex]\(70000\)[/tex]
Standard Deviation (rounded to the nearest whole number): [tex]\(265\)[/tex]
Therefore, to fill in the given blanks:
- What is the variance? [tex]\( \boxed{70000} \)[/tex]
- What is the standard deviation, rounded to the nearest whole number? [tex]\( \boxed{265} \)[/tex]
