Step 1: Find the mean lifetime of Brand A.
For Brand A, the observations are
\[
27,28,30,32,33
\]
The sample mean is
\[
\bar{x}_A=\frac{27+28+30+32+33}{5}
\]
\[
\bar{x}_A=\frac{150}{5}=30
\]
Step 2: Find the sample standard deviation of Brand A.
The deviations from mean are
\[
-3,-2,0,2,3
\]
The sum of squares of deviations is
\[
(-3)^2+(-2)^2+0^2+2^2+3^2
\]
\[
=9+4+0+4+9=26
\]
Since sample variance uses denominator \(n-1\),
\[
s_A^2=\frac{26}{5-1}
\]
\[
s_A^2=\frac{26}{4}=\frac{13}{2}
\]
Thus,
\[
s_A=\sqrt{\frac{13}{2}}
\]
Step 3: Find the mean lifetime of Brand B.
For Brand B, the observations are
\[
17,19,20,21,23
\]
The sample mean is
\[
\bar{x}_B=\frac{17+19+20+21+23}{5}
\]
\[
\bar{x}_B=\frac{100}{5}=20
\]
Step 4: Find the sample standard deviation of Brand B.
The deviations from mean are
\[
-3,-1,0,1,3
\]
The sum of squares of deviations is
\[
(-3)^2+(-1)^2+0^2+1^2+3^2
\]
\[
=9+1+0+1+9=20
\]
Thus,
\[
s_B^2=\frac{20}{5-1}
\]
\[
s_B^2=5
\]
So,
\[
s_B=\sqrt{5}
\]
Step 5: Compare sample standard deviations.
Since
\[
s_A=\sqrt{\frac{13}{2}}=\sqrt{6.5}
\]
and
\[
s_B=\sqrt{5}
\]
we get
\[
s_A>s_B
\]
Step 6: Compare coefficients of variation.
The sample coefficient of variation is
\[
CV=\frac{s}{\bar{x}}
\]
For Brand A,
\[
CV_A=\frac{s_A}{30}
=
\frac{\sqrt{\frac{13}{2}}}{30}
\]
For Brand B,
\[
CV_B=\frac{s_B}{20}
=
\frac{\sqrt{5}}{20}
\]
To compare, square both positive quantities.
\[
CV_A^2=\frac{\frac{13}{2}}{900}
=
\frac{13}{1800}
\]
and
\[
CV_B^2=\frac{5}{400}
=
\frac{1}{80}
\]
Now,
\[
\frac{13}{1800}<\frac{1}{80}
\]
because
\[
13\times 80=1040<1800
\]
Therefore,
\[
CV_A<CV_B
\]
Step 7: Final conclusion.
Hence,
\[
CV_A<CV_B
\]
and
\[
s_A>s_B
\]
Therefore, the correct option is
\[
\boxed{(B)}
\]