Concept:
The mean of a set of observations is the average of all values, while the variance measures the spread of the observations around the mean.
For $n$ observations $x_1,x_2,\dots,x_n$:
\[
\mu=\frac{\sum x_i}{n}
\]
and
\[
\sigma^2=\frac{\sum (x_i-\mu)^2}{n}
\]
Step 1: Finding the mean of the given observations.
The observations are:
\[
2,\ 4,\ 6,\ 8,\ 10
\]
Their sum is:
\[
2+4+6+8+10=30
\]
Number of observations:
\[
n=5
\]
Therefore,
\[
\mu=\frac{30}{5}=6
\]
Step 2: Calculating deviations from the mean.
The deviations from the mean are:
\[
2-6=-4
\]
\[
4-6=-2
\]
\[
6-6=0
\]
\[
8-6=2
\]
\[
10-6=4
\]
Step 3: Squaring the deviations.
\[
(-4)^2=16
\]
\[
(-2)^2=4
\]
\[
0^2=0
\]
\[
2^2=4
\]
\[
4^2=16
\]
Sum of squared deviations:
\[
16+4+0+4+16=40
\]
Step 4: Finding the variance.
\[
\sigma^2=\frac{40}{5}=8
\]
Step 5: Finding the required value.
\[
\mu+\sigma^2=6+8=14
\]
\[
\boxed{14}
\]