What is the consequence of a Type I error concluding that a treatment has an effect when it really does?
Rejecting a true null hypothesis. What is the consequence of a Type I error? Concluding that a treatment has an effect when it really has no effect.
What hypothesis states no difference or no effect?
The null hypothesis states that the treatment has no effect. In general the null hypothesis states that there is no change, no difference, no effect, and otherwise no relationship between the independent and dependent variables. Because we are hypothesizing that nothing is happening, it is called the null hypothesis.
When the researcher rejects a true null hypothesis?
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.
What is the consequence of a Type 2 error quizlet?
A Type II error occurs when a researcher concludes that a treatment has an effect but, in fact, the treatment has no effect.
What does hypothesis of no difference mean?
The null hypothesis states that there is no difference or association. With hypothesis testing, the null hypothesis states that there is no difference or association between variables of interest.
How do you interpret the rejection of the null hypothesis?
Rejecting the Null Hypothesis Reject the null hypothesis when the p-value is less than or equal to your significance level. Your sample data favor the alternative hypothesis, which suggests that the effect exists in the population. For a mnemonic device, remember—when the p-value is low, the null must go!
What is the outcome when a null hypothesis has been rejected and the null hypothesis is true?
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 .
What is the outcome when you reject the null hypothesis when it is false?
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 happens when a null hypothesis has been accepted and the null hypothesis is really false?
If the null hypothesis is false, there is a 1-β probability that we will make the right choice and reject it. The probability that we will make the right choice when the null hypothesis is false is called statistical power.
What is a consequence of a type II error?
A type II error is a statistical term used within the context of hypothesis testing that describes the error that occurs when one fails to reject a null hypothesis that is actually false. A type II error produces a false negative, also known as an error of omission.
What is a consequence of a type 1 error?
Consequences of a Type I Error A type I error will result in a false alarm. The outcome of the hypothesis testing will be a false positive. This implies that the researcher decided the result of a hypothesis testing is true when in fact, it is not.
What are Type 1 and Type 2 errors quizlet?
Terms in this set (4) Type I error. False positive: rejecting the null hypothesis when the null hypothesis is true. Type II error. False negative: fail to reject/ accept the null hypothesis when the null hypothesis is false.