Help with Writing null & alternative Hypotheses

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In summary, the researcher believes that mice will move faster through a maze when subjected to a loud noise. The null hypothesis states that the mean travel time is not less than 29 seconds, while the alternate hypothesis states that the mean travel time is less than 29 seconds. The number of samples used will determine whether there is enough evidence to support the null or alternate hypothesis.
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Homework Statement



After extensive investigation, a researcher has found that the mean travel
time for mice through one particular maze is 29.0 seconds. She believes
that the mice will move faster through the maze when subjected to a loud
noise. In order to assess this, the researcher has run 17 mice separately
through the same maze, in the presence of such a noise, and recorded the
times taken. These produced a sample mean travel time of ¯x = 27.84 and a
sample standard deviation of s = 1.73 . (You may assume that the population
distribution is N(μ, σ2).)
(i) State the relevant null and alternative hypotheses, in terms of a suitable
parameter, in order to answer the question: Is there enough evidence to
suggest that the mean travel time is less than 29 seconds?


The Attempt at a Solution




I'm not sure if this is correct, could you please give me pointers on anything that I have missed?

H0: The number of samples n is sufficiently large enough to suggest that the sample mean ¯x accurately reflects the mean travel time when a loud noise is present.

H1: The number of samples n is not large enough to accurately suggest that the sample mean ¯x accurately reflects the mean travel time when a loud noise is present.



any pointers? I'm not very good at this, cheers.
 
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You seem to be completely misunderstanding what a "hypothesis" is. The null hypothesis and alternate hypothesis have nothing to do with the number of samples.
A researcher always determines the null and alternate hypotheses before deciding how many samples to use.

"She believes that the mice will move faster through the maze when subjected to a loud noise." Her "null hypothesis", then, is "the mean time required to run the maze with a loud noise is NOT less than the mean time without the loud noise".

The number of trials determines whether or not the data is sufficient to support the null or alternate hypotheses.
 

What is a null hypothesis?

A null hypothesis is a statement that there is no significant difference or relationship between two variables in a statistical analysis. It is typically denoted as H0.

What is an alternative hypothesis?

An alternative hypothesis is a statement that there is a significant difference or relationship between two variables in a statistical analysis. It is typically denoted as H1 or Ha.

How do you write null and alternative hypotheses?

Null and alternative hypotheses should be written as clear and testable statements. The null hypothesis should state that there is no significant difference or relationship between the variables, while the alternative hypothesis should state that there is a significant difference or relationship between the variables. For example, "There is no significant difference in test scores between students who study for 2 hours and those who study for 4 hours" would be the null hypothesis, while "There is a significant difference in test scores between students who study for 2 hours and those who study for 4 hours" would be the alternative hypothesis.

What is the purpose of null and alternative hypotheses?

The purpose of null and alternative hypotheses is to provide a framework for statistical testing. By comparing the data collected to the null hypothesis, we can determine if there is enough evidence to reject the null hypothesis and support the alternative hypothesis. This allows us to make conclusions about the relationship between variables and draw meaningful conclusions from our data.

What is the difference between one-tailed and two-tailed hypotheses?

One-tailed hypotheses only test for a difference in one direction, while two-tailed hypotheses test for a difference in both directions. For example, a one-tailed hypothesis might state that "Students who study for 4 hours will score higher on the test than students who study for 2 hours". A two-tailed hypothesis, on the other hand, might state that "There is a difference in test scores between students who study for 2 hours and those who study for 4 hours". The choice between one-tailed and two-tailed hypotheses should be based on the research question and the direction of the expected difference or relationship.

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