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How do you determine reject or fail to reject?
Suppose that you do a hypothesis test. Remember that the decision to reject the null hypothesis (H 0) or fail to reject it can be based on the p-value and your chosen significance level (also called α). If the p-value is less than or equal to α, you reject H 0; if it is greater than α, you fail to reject H 0.
What is it called when the null hypothesis is false and you reject the null hypothesis?
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.
What does it mean to reject or fail to reject the hypothesis?
After you perform a hypothesis test, there are only two possible outcomes. When your p-value is less than or equal to your significance level, you reject the null hypothesis. Your results are statistically significant. When your p-value is greater than your significance level, you fail to reject the null hypothesis.
How do you accept or reject the null hypothesis?
Set the significance level, , the probability of making a Type I error to be small — 0.01, 0.05, or 0.10. Compare the P-value to . If the P-value is less than (or equal to) , reject the null hypothesis in favor of the alternative hypothesis. If the P-value is greater than , do not reject the null hypothesis.
What statement do we make that determines if the null hypothesis is rejected?
If there is less than a 5\% chance of a result as extreme as the sample result if the null hypothesis were true, then the null hypothesis is rejected. When this happens, the result is said to be statistically significant .
How do you reject the null hypothesis with p-value?
If the p-value is less than 0.05, we reject the null hypothesis that there’s no difference between the means and conclude that a significant difference does exist. If the p-value is larger than 0.05, we cannot conclude that a significant difference exists.
What is the reason of a null hypothesis being rejected?
If the sample with the added chemical is measurably more or less acidic-as determined through statistical analysis-it is a reason to reject the null hypothesis. If the sample’s acidity is unchanged, it is a reason to not reject the null hypothesis. When scientists design experiments, they attempt to find evidence for the alternative hypothesis.
When should you accept a null hypothesis?
A high statistical power does not allow you to “accept” the null hypothesis. If you find yourself wanting to “prove” the null hypothesis when you are testing whether one variable affects another in a meaningful way, the proper way to do it is through equivalence testing.
What does rejecting your null hypothesis mean?
The null hypothesis states there is no significant difference in outcomes between the control (untreated) and the treatment condition. To reject the null hypothesis is to say that there is a significant difference. In other words, the treatment obtains better results than doing nothing.
Does hypothesis test ever prove a null hypothesis?
A significance test is used to establish confidence in a null hypothesis, and to determine the possibility that the observed data is not due to chance or manipulation of data. Researchers test the hypothesis by examining a random sample of the plants being grown with or without sunlight.