Hypothesis Testing Flashcards
What is “Hypothesis Testing” ?
The process of testing of hypotheses about one or more populations using statistical inference.
What is a “Hypothesis”?
A proposed explanation or theory that can be tested.
What is a “Null Hypothesis” ?
The hypothesis that is tested.
What is an “Alternative Hypothesis” ?
The hypothesis that is accepted if the null hypothesis is rejected.
What is “Type 1 Error”?
The error or rejecting a true null hypothesis;
A false positive.
What is “Type 2 Error”?
The error of not rejecting a false null hypothesis; false negative.
What is “Level of Significance” ?
The probability of a Type 1 error in testing a hypothesis.
What is a “Confidence Level”?
The complement of “Level of Significance”
What is the “Power of a test” ?
The probability of correctly rejecting the null - that is, rejecting the null hypothesis when it is false.
What are “Critical Values” ?
Values of the test statistic at which the decision changes “from fail to reject the null hypothesis” to “reject the null hypothesis”
What does “Statistically Significant” mean?
A result indicating that the null hypothesis can be rejected; with reference to an estimated regression coefficient; frequently understood to mean a result indicating that the corresponding population regression coefficient is different than zero.
What is a “p-Value” ?
The smallest level of significance at which the null is rejected.
What is a “Test of the mean of the differences” ?
A statistical test for differences based on paired observations drawn from samples that are dependent on each other.
What is a “Parametric Test”?
Any test (or procedure) concerned with parameters or whose validity depends on assumptions concerning the population generating the sample.
What is a “Non-parametric Test”?
A test that is not concerned with a parameter or that makes minimal assumptions about the population from which a sample comes.
