Module 2: Hypotheses & Statistical Inference Flashcards
Define null hypothesis.
The null hypothesis is a specific statement about a population parameter made for the purposes of arguing a skeptical or uninteresting point of view.
Define alternative hypothesis.
The alternative hypothesis is a nonspecific statement about a population parameter that includes all feasible values besides the uninteresting point of view of the null hypothesis.
Define test statistic.
The test statistic is a number calculated from the data that is used to evaluate how compatible the data are with the result expected by the null hypothesis.
Define significance level.
Define null distribution.
Define type I error.
Define type II error.
Define power.
Define P-value.
What are the four steps of hypothesis testing?
- State the hypotheses.
- Compute the test statistic.
- Determine the P-value.
- Draw the appropriate conclusions.
How are appropriate null and alternative hypotheses constructed?
The null hypothesis states that the population parameter is zero (ex. no effect, no difference). Alternatively, it may represent some expectation from prior theory. The alternative hypothesis states that the population parameter is anything other than zero, or the opposing claim to the null hypothesis.
What is the difference between one and two-sided hypotheses and when is each one appropriate?
A two-sided hypothesis allows for two possible parameter values on both sides of the parameter value specified in the null hypothesis.
Why is sampling error the source of variation in null distributions?
How does sampling error allow for the rejection of a null hypothesis?
How are the results of a statistical test reported?
