Determine the rejection region in the problem involving hypothesis

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In summary, Ms Solution shared her approach for solving a problem with a confidence level of 0.975 and a given value of -1.96 for the Z-score. Based on this, the value of X was calculated to be 43.7. Further explanation was provided on the use of Z-score in this problem.
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chwala
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Homework Statement
See attached
Relevant Equations
stats
1654294489085.png


Ms Solution

1654294537427.png


My approach is just the same as ms...

The thing to note is that at ##0.975= Z_{[-1.96]}##

therefore we shall have,

##-1.96=\left[\dfrac{X-45.7}{\dfrac{5.6}{\sqrt 30}}\right]=\dfrac{X-45.7}{1.022415441}##

##-1.96×1.022415441=X-45.7##

##X=-2.003934+45.7=43.7##

Any insight is welcome.
 
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Hello Ms Solution,

Thank you for sharing your approach with us. I agree with your calculations and conclusion that the value of X is 43.7. To provide further insight, I would like to explain the reasoning behind the use of the Z-score in this problem.

The Z-score is a measure of how many standard deviations a data point is above or below the mean. In this case, we are given the confidence level of 0.975, which corresponds to a Z-score of -1.96. This means that the data point (X) we are looking for is 1.96 standard deviations below the mean of 45.7.

To solve for X, we use the formula for the Z-score, which is (X - mean) / standard deviation. In this case, the mean is 45.7 and the standard deviation is 5.6 / √30. By substituting these values into the formula and solving for X, we get the same result as you did.

I hope this provides a better understanding of the use of Z-score in this problem. Thank you for sharing your approach and opening the discussion for further insights. Keep up the great work!
 

FAQ: Determine the rejection region in the problem involving hypothesis

What is a rejection region?

A rejection region is a range of values that, if obtained from a statistical test, would lead to the rejection of the null hypothesis. It is typically determined based on the desired level of significance and the distribution of the test statistic.

Why is it important to determine the rejection region?

Determining the rejection region is important because it helps us make decisions about the validity of our hypothesis. If the test statistic falls within the rejection region, we can reject the null hypothesis and conclude that there is a significant difference between the observed data and the expected results.

How is the rejection region determined?

The rejection region is determined by first choosing a desired level of significance, denoted by alpha (α). This is the probability of obtaining a test statistic that falls within the rejection region when the null hypothesis is actually true. The rejection region is then determined based on the distribution of the test statistic and the chosen alpha level.

Can the rejection region change for different hypothesis tests?

Yes, the rejection region can change for different hypothesis tests. The specific distribution of the test statistic and the chosen alpha level can vary between different tests, resulting in different rejection regions. It is important to determine the appropriate rejection region for each specific hypothesis test.

What happens if the test statistic falls within the rejection region?

If the test statistic falls within the rejection region, we can reject the null hypothesis. This means that there is a significant difference between the observed data and the expected results, and we can conclude that the alternative hypothesis is supported.

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