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

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The discussion focuses on testing the assumption that a specific car model achieves at least 120 km per liter of gasoline. The null hypothesis is correctly stated as H0: μ = 120, while the alternative hypothesis should be H1: μ ≥ 120, reflecting the "at least" condition. Participants clarify that the alternative hypothesis must include an inequality due to the wording of the assumption, indicating a one-sided test. The conversation emphasizes the importance of accurately defining hypotheses based on the context provided. Understanding these concepts is crucial for conducting a valid statistical test.
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". 🧐
 
The standard _A " operator" maps a Null Hypothesis Ho into a decision set { Do not reject:=1 and reject :=0}. In this sense ( HA)_A , makes no sense. Since H0, HA aren't exhaustive, can we find an alternative operator, _A' , so that ( H_A)_A' makes sense? Isn't Pearson Neyman related to this? Hope I'm making sense. Edit: I was motivated by a superficial similarity of the idea with double transposition of matrices M, with ## (M^{T})^{T}=M##, and just wanted to see if it made sense to talk...

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