Respuesta :
There is sufficient data to infer that the valve does not operate as intended at the 0.1 level.
Null hypothesis: H₀ : μ = 7.6
Alternative hypothesis: Hₐ : μ ≠ 7.6
What is the Null hypothesis?
In inferential statistics, the null hypothesis states that two possibilities are equal.
The observed difference is thought to be the sole product of chance, which is the underlying premise.
Statistical tests can be used to calculate the likelihood that the null hypothesis is true.
So,
Null hypothesis: H₀ : μ = 7.6
Alternative hypothesis: Hₐ : μ ≠ 7.6
As the population standard deviation is given when n > 30
So, we'll run the Z test.
Formula: [tex]z=\frac{x-\mu}{\frac{a}{\sqrt{n}}}[/tex]
Replace the values:
[tex]\begin{aligned}& z=\frac{7.7-7.6}{\frac{11.6}{\sqrt{160}}} \\& z=2.449\end{aligned}[/tex]
For the p-value, see the z table.
Consequently, p = 0.9927.
The two-tailed nature of the test So, p = 2(1- 0.9927) = 0.0146
α = 0.1
p value< α
Thus, we disregard the null hypothesis.
Hence, at the 0.1 level, there is enough evidence to conclude that the valve does not function as intended.
Therefore, there is sufficient data to infer that the valve does not operate as intended at the 0.1 level.
Null hypothesis: H₀ : μ = 7.6
Alternative hypothesis: Hₐ : μ ≠ 7.6
Know more about the Null hypothesis here:
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