Descriptive statistics and inferential statistics are both important components of statistics when learning about a population.
Hypothesis tests and confidence intervals are related, but have some important differences.
Different statistical tests are used to test quantitative and qualitative data.
Different statistical tests are required when there are different numbers of groups (or samples).
Results are deemed significant if they are found to have occurred by some reason other than chance.
Testing hypothesis once you've seen the data may result in inaccurate conclusions.
The results are deemed important if they change the effects of an event.
A statistical model is a set of assumptions concerning the generation of the observed data and similar data.
Rejecting the null hypothesis does not necessarily prove the alternative hypothesis.