Hypothesis testing
The theory, methods, and practice of testing a hypothesis by comparing it with the null hypothesis
Null hypothesis
The hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error.
Alternative hypothesis
The statement that is being tested against the null hypothesis is the alternative hypothesis. Usually, the alternative hypothesis states that two groups are statistically significant.
Nondirectional hypothesis
A non-directional (two-tailed) hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified.
Directional hypothesis
A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place.
If the p-value is greater than α, then we _____.
fail to reject the null hypothesis
If the p-value is less than α, then we _____ and _____.
reject the null hypothesis and state that there is a statistically significant difference between the two groups
When the null hypothesis is rejected, we state that our results are _____.
statistically significant
Type I error
A type I error (α) is the likelihood that we report a difference between two populations when one does not actually exist.
Type II error
A type II error (β) is the likelihood that we report no difference between two populations when one actually exists.
Power
The probability of a type II error is sometimes symbolized by β. The probability of correctly rejecting a false null hypothesis (reporting a difference between two populations when one actually exists) is referred to as power, and is equal to 1 − β.
Power (statistics) equation
1 − β
Confidence
The probability of correctly failing to reject a true null hypothesis (reporting no difference between two populations when one does not exist) is referred to as confidence.
Confidence interval
A confidence interval refers to the probability that a population parameter will fall between a set of values for a certain proportion of times.
Confidence interval equation
