A Question about Hypothesis Testing

In summary, hypothesis testing is a statistical method used to determine the validity of a hypothesis or claim about a population based on a sample of data. It involves comparing the observed data to what would be expected if the null hypothesis were true. A null hypothesis is the default assumption in hypothesis testing, assuming no significant difference between groups or variables being compared. In contrast, an alternative hypothesis assumes a significant difference between groups or variables. The significance level, also known as alpha, is the probability of rejecting the null hypothesis when it is actually true. A p-value is the probability of obtaining results at least as extreme as the observed data, assuming the null hypothesis is true, and is used to determine the statistical significance of the results.
  • #1
Artusartos
247
0
In this link:

http://www.math.harvard.edu/~phorn/362/362assn3-solns.pdf

Why isn't the significane level for number 5 just 0.01? Because we know that if the mean is 30,000 (the same as the mean for the null hypothesis), the value of the power function is 0.01...

Thanks in advance
 
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  • #2
Are you sure you added the correct link? I cannot see 30,000 or 0.01 anywhere at problem 5 (or anywhere else).
 

Related to A Question about Hypothesis Testing

1. What is hypothesis testing?

Hypothesis testing is a statistical method used to determine the validity of a hypothesis or claim about a population based on a sample of data. It involves comparing the observed data to what would be expected if the null hypothesis (the default assumption) were true.

2. What is a null hypothesis?

A null hypothesis is a statement that assumes there is no significant difference between groups or variables being compared. It is the default assumption in hypothesis testing and is usually denoted as H0.

3. What is an alternative hypothesis?

An alternative hypothesis is a statement that assumes there is a significant difference between groups or variables being compared. It is the alternative to the null hypothesis and is usually denoted as H1.

4. What is the significance level in hypothesis testing?

The significance level, also known as alpha (α), is the probability of rejecting the null hypothesis when it is actually true. It is typically set at 0.05 or 0.01, depending on the level of certainty required in the results.

5. What is a p-value in hypothesis testing?

A p-value is the probability of obtaining results at least as extreme as the observed data, assuming the null hypothesis is true. It is used to determine the statistical significance of the results, with a smaller p-value indicating stronger evidence against the null hypothesis.

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