Course content

In this course, you will learn to work with the core concepts and techniques of descriptive and inferential statistics that function as foundations for formulating and implementing successful data-based analysis strategies to perform evidence-based research.

You will be introduced to the essentials of basic programming and use of syntax-based data analysis as instantiated in the open-source statistical and graphic software environment R.

The course covers the following five key topics:

1. Data Management: wrangling & auditing

2. Descriptive Statistics

3. Data Visualization and Representations (i.e., plots, tables, diagrams)

4. Probability and Randomness

5. Statistical Inference & Design

Throughout the course, attention will be given to issues regarding questionable research practices and research ethics.

Learning outcome

Knowledge

  • recognize the challenges with respect to data collection, data quality, and alignment between research questions and the data
  • recognize descriptive statistics as basic summaries of specific data features
  • recognize that sampling variability and uncertainty are ubiquitous

Skills

  • run basic data mana