Table of Contents
- 1 What does it mean to fail to reject the hypothesis?
- 2 What does it mean to falsely reject the null hypothesis?
- 3 What does it mean to support or reject a hypothesis?
- 4 What type of error occurs if you fail to reject the null hypothesis when it is not true?
- 5 When we fail to reject a false null hypothesis What error has been made?
- 6 Is there enough evidence to reject the claim?
What does it mean to fail to reject the hypothesis?
Failing to reject the null indicates that our sample did not provide sufficient evidence to conclude that the effect exists. However, at the same time, that lack of evidence doesn’t prove that the effect does not exist.
What does it mean to falsely reject the null hypothesis?
type 1 error
A type 1 error is also known as a false positive and occurs when a researcher incorrectly rejects a true null hypothesis. This means that your report that your findings are significant when in fact they have occurred by chance. For example, a p-value of 0.01 would mean there is a 1% chance of committing a Type I error.
What does it mean to support or reject a hypothesis?
Support or reject null hypothesis? If the P-value is less, reject the null hypothesis. If the P-value is more, keep the null hypothesis. 0.003 < 0.05, so we have enough evidence to reject the null hypothesis and accept the claim.
What does it mean if I fail to reject the null hypothesis for a one sample z test?
If the p-value is greater than the significance level, the decision is to fail to reject the null hypothesis. You do not have enough evidence to conclude that the difference between the population mean and the hypothesized mean is statistically significant.
What happens if you fail to reject the null hypothesis?
When we reject the null hypothesis when the null hypothesis is true. When we fail to reject the null hypothesis when the null hypothesis is false. The “reality”, or truth, about the null hypothesis is unknown and therefore we do not know if we have made the correct decision or if we committed an error.
What type of error occurs if you fail to reject the null hypothesis when it is not true?
When the null hypothesis is false and you fail to reject it, you make a type II error. The probability of making a type II error is β, which depends on the power of the test. You can decrease your risk of committing a type II error by ensuring your test has enough power.
When we fail to reject a false null hypothesis What error has been made?
If the null hypothesis is false, then it is impossible to make a Type I error. The second type of error that can be made in significance testing is failing to reject a false null hypothesis. This kind of error is called a Type II error. Unlike a Type I error, a Type II error is not really an error.
Is there enough evidence to reject the claim?
The p-value is the probability of observing such a sample mean when the null hypothesis is true. If the probability is too small (less than the level of significance), then we believe we have enough statistical evidence to reject the null hypothesis and support the alternative claim.