Statistically significant repetition 2404-P-MF-RSI

INTRODUCTION
Statistics is not only a collection of tools needed to write a thesis, but also the glasses through which we look at the world of phenomena.
In this class we will organize our knowledge of descriptive statistics and recall information about statistical techniques. We will primarily deal with classical statistics, which is firmly rooted in the normal distribution and the frequency interpretation of probability. We will dust off the mechanics of classical tests and make sense of concepts such as p-value, statistical significance, effect size. We will answer questions about whether a statistically significant correlation is a large correlation. Can the researcher be sure that there are no differences between groups.

SCOPE of classes:
- descriptive statistics
- classical tests of statistical significance:
- correlation analysis (primarily r-Pearson and rho-Spearman)
- Student's t-test (independent groups and its non-parametric equivalent)
- linear (multiple) regression
- power analysis (answering the question, how many people do I need for the statistical test used to have a power of .80%)

In addition to discussing the aforementioned methods, we will remind you of the order in which to perform the steps in SPSS.

If there is enough time we will also touch on other techniques from basic statistics 1-2 and analysis of variance (univariate, primarily post-hoc tests)
What there won't be: moderation and mediation analysis, analysis of covariance, structural equations, learning statistical packages other than SPSS (R, AMOS, Python). The repetition covers only the very basics of statistics.