Full course description
At the end of this course, students should be familiar with the basic concepts of inferential statistics, and will be able to perform basic statistical analyses in a variety of scenarios. In most scientific research, researchers have to deal with the problem of drawing conclusions about a population characteristic of interest, relying only on a sample of observations from that population. Inferential statistics is a way to tackle this problem. This course starts by covering the foundations of inferential statistics, emphasizing the logic behind the statistical reasoning process. This logic is the basis for explaining a number of widely used applied statistical methods: ANOVA, Chi-square and Nonparametric tests. Students will learn how to run each of these methods using the statistical software package SPSS. Additionally, they will learn how to determine the required number of observations needed to be able to show, with a fixed probability, a specified research hypothesis.
- To enhance students’ understanding of the basics of inferential statistics.
- To broaden the scope of statistical methods that students are acquainted with by introducing a number of widely used applied tests.
- To understand how researchers determine required sample sizes for a number of (simple) designs and to be able to apply these methods.
- To familiarize students with statistical software, so that they can independently run the analyses that are covered in this course and are able to correctly interpret the corresponding output.
- Statistics for the Life Sciences (5th ed.) by Samuels, M.L., Witmer, J.A. & Schaffner, A. Publisher: Pearson (2016).