Stats Flashcards
Normal distribution with a known variance, n < 30
Z statistic
Normal distribution with a known variance, n>30
Z statistic
Normal distribution with an unknown variance, n<30
t statistic
Normal distribution with an unknown variance, n>30
t statistic* *you can use the z statistic here but t statistic is more conservative and therefore more preferred
Nonnormal distribution with a known variance, n<30
not available
Nonnormal distribution with a known variance, n>30
Z statistic
Nonnormal distribution with an unknown variance, n<30
not available
Nonnormal distribution with an unknown variance, n>30
t statistic* *you can use the z statistic here but t statistic is more conservative and therefore more preferred
Type I Error
Type I Error is when you reject the null Hypothesis when it’s true
Type II Error
Type II Error is when you fail to reject a false null Hypothesis
Power of a test
Power of a test is the probability of correctly rejecting a false null hypothesis
When level of significance is 10%, the Z values will be
For 2-tailed test: 1.65 For 1-tailed test: 1.28
When level of significance is 5%, the Z values will be
For 2-tailed test: 1.96 For 1-tailed test: 1.65
When level of significance is 1%, the Z values will be
For 2-tailed test: 2.576 For 1 tailed test: 2.33
The chi-square test is used for
A chi-square statistic is used to test a hypothesis about the variance of a single population.
When testing a hypothesis about the equality of variances of two normally distributed populations, you use
F-statistic
Parametric tests
Parametric tests rely on assumptions regarding the distribution of the population and are specific to population parameters.
Nonparametric tests
Nonparametric tests either do not consider a particular population parameter or have few assumptions about the population that is sampled. Nonparametric tests are used when there is concern about quantities other than the parameters of a distribution or when the assumptions of parametric tests can’t be supported. They are also used when the data are not suitable for parametric tests (e.g., ranked observations).
decision for 2-tailed test
Reject H0 if: -(test statistic) < lower critical value
upper critical value < test statistic
Decision for 1-tailed test
