Quantitative methods

Type of course: Methods

The course introduces the most common statistical methods to analyse quantitative data.

The course aims to give students an overview of methods available for analyzing quantitative data.

The course will cover main methods for analyzing relationships between

(a) continuous predictor and continuous outcome variables

(b) continuous predictor and categorical outcome variables

(c) categorical predictor and continuous outcome variables

(d) categorical predictor and categorical outcome variables.

In addition, it will be introduced in which conditions must be met to use parametric methods and when one has to use non-parametric methods.

Knowledge

After completion of the course, the candidate has knowledge of the most common statistical methods to analyze quantitative data. An overview will be given about what are categorical and continuous data as well as what are predictor and outcome variables. Afterwards this terminology will be used to introduce methods for analyzing relationships within the four possible combinations of categorical vs. continuous and predictor vs. outcome variables:

[a] continuous predictor and continuous outcome variables (correlation and linear regression)

[b] continuous predictor and categorical outcome variables (logistic regression)

[c] categorical predictor and continuous outcome variables (analysis of variance)

[d] categorical predictor and categorical outcome variables (chi-squared)

In addition, it will be introduced which conditions have to be met to use parametric methods and when one has to use non-parametric methods.

Skills

After completion of the course, the candidate will be able:

[a] to prepare data collection in a way that makes evaluation of these data as easy as possible

[b] to select an appropriate evaluation method

[c] to carry these out in a software package for statistical analyses.

General competence

After completion of the course, the candidate will

[a] be able to organize own data

[b] have basic knowledge about how to handle missing data

[c] be able to choose an appropriate method to evaluate these data statistically

[d] have knowledge about how to carry out common statistical procedures. This knowledge will also enable the candidate to critically reflect upon methods used by other researcher in publications.

Autumn 2023

Course dates: 20, 24, 30 November & 4 December