$~ 10 ~$ samples were sampled from the glass partitions.
Each value of the following represents a refractive index of it.
$$ 1.77,~1.79,~1.78,~1.79,~1.79,~1.76,~1.8,~1.76,~1.79,~1.80 $$
As the standard deviation of refractive indices is less than or equal to $~ 0.008 ~$, the acceptance test can be passed, otherwise fails.
Judge the acceptability of the glasses with $~ \alpha=0.01 ~$
$$ \begin{cases} \color{fuchsia}{H_0:\sigma^2=0.008^2} \\H_1:\sigma^2>0.008^2\end{cases} $$
I think that the null-hypothesis should be $~ H_0:\sigma^2 \leq 0.008^2 ~$ since it is too diffuclt to infer the exact true variance of the population(infinite size?)
The table of test-statistics which attaches to the book of this problem statement only handles cases where null-hypotheses take exact values.
I am really confusing.
Can anyone tell me why the pink eqn is adequate?
The statement in words is the standard deviation of refractive indices is less than or equal to $0.008$, the acceptance test can be passed, otherwise fails.
So the null hypothesis that you are testing and might reject is $H_0: \sigma \le 0.008$. If the null hypothesis is in fact true, you want to reject it with probability no greater than $\alpha$.
Clearly in this example you are going to say the test fails if the sample standard deviation is too high, for example if the sample standard deviation $s_n$ exceeds some value $k$, where $k$ is determined by $\alpha$, the sample size and the value in the null hypothesis. This will give you the most powerful test.
If the null hypothesis is in fact true, you want $\mathbb P(s_n>k)\le \alpha$. Since $\mathbb P(s_n>k)$ is an increasing function of $\sigma$, the smallest value of $k$ which ensures $\mathbb P(s_n>k)\le \alpha$ for all $ \sigma \le 0.008$ is that which occurs when $\sigma=0.008$. So you use that point value to decide $k$ and the critical region.
There is another issue to think about: you have data rounded to $0.01$ but are testing a standard deviation of $0.008$ so the result will be affected by the rounding.