Testing the Assumption of Car Model's km/L Performance

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SUMMARY

The discussion centers on hypothesis testing for a car model's fuel efficiency, specifically testing the assumption that it achieves at least 120 km per liter of gasoline. The null hypothesis is established as $H_0: \mu = 120$, while the alternative hypothesis is correctly identified as $H_1: \mu \geq 120$. The tests conducted yielded results that necessitate calculating the p-value and determining the confidence level at which the null hypothesis can be rejected. The conversation emphasizes the importance of correctly framing the alternative hypothesis based on the wording of the assumption.

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mathmari
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Hey! :giggle:

Some people assume that a specific car model does at least $\mu_0=120$ km with $1$ Lt benzin.

$10$ independent tests give the following results: $$104, \ 96, \ 80, \ 100, \ 108, \ 100, \ 112, \ 120, \ 130, \ 132$$

(a) Give the Null Hypothesis $H_0$ and the alternative Hypothesis $H_1$, for the test of that assumption.

(b) Give the statistic function of that test.

(c) late the p-value of the test.

(d) In what confidence level can the assumption be rejected?
For (a) is the null hypothesis $H_0: \ m_0=120$ and the alternative $H_1: \ \mu_1\neq 120$ ?
 
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mathmari said:
Some people assume that a specific car model does at least $\mu_0=120$ km with $1$ Lt benzin.

(a) Give the Null Hypothesis $H_0$ and the alternative Hypothesis $H_1$, for the test of that assumption.

For (a) is the null hypothesis $H_0: \ m_0=120$ and the alternative $H_1: \ \mu_1\neq 120$ ?
Hey mathmari!

The assumption says "at least". We're not covering that with $\mu_1\ne 120$. 🤔
 
Klaas van Aarsen said:
The assumption says "at least". We're not covering that with $\mu_1\ne 120$. 🤔

So the assumption should be at the alternative hypothesis, or not?

So is it $H_1: \ \mu_1\geq 120$ ? :unsre:
 
mathmari said:
So the assumption should be at the alternative hypothesis, or not?

So is it $H_1: \ \mu_1\geq 120$ ? :unsre:
Yep. (Nod)

Generally, if the problem statement contains a word like "less than", "more", or "at least", then we need an inequality in the alternative hypothesis.
It also means that the test is "one-sided". 🧐
 

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