Introduction to Statistics
Basic skills in programming with R (can be achieved in the course Introduction to R).
“Introduction to Statistics” is a foundational course in statistical analysis for scientists and practitioners. This introductory course combines an overview of basic statistical methods with their application in the statistical software R. This course covers descriptive statistics, classical statistical tests, and linear regression and its extensions. All methods are explained in an applied setting. By the end of the course, you will be able to identify appropriate statistical methods, apply them, and interpret your results.
This course does not require any previous knowledge of statistics.
The course covers basic statistical methods
- Descriptive statistics
- Levels of variables
- Measures of tendency and variability (mean, median, variance, …)
- Classical statistical graphics and when to apply them (histogram, boxplots, violin plots, …)
- Random variables
- Distribution of random variables
- Characteristics of distributions
- Confidence intervals
- Hypothesis testing
- How to apply tests
- Classical statistical test (t-test, Wilcoxon-test, ANOVA, ...)
- When to apply which test
- Multiple testing and corrections
- Linear regression
- Idea of linear regression
- How to apply and interpret linear models
- Limits of linear regression
- The focus in all chapters is to understand when to apply which method, how to run them in R and how to interpret the output. Also, limitations and extensions of the methods are discussed.
This is no introductory programming course. Basic programming skills in R are a prerequisite of this course and can be achieved with the course Introduction to R.
- Each day consists of blocks covering first the statistical theory behind the methods and their application in R, and then hands-on examples with best-practice solutions.
- Duration: 4 Days
- Language: English
- This course will be offered either on campus (in person), or online.
- For online courses we use the software Zoom.
- Material for the course can be found here* .
- Please install the necessary R-packages prior to the course. The packages are listed in "Material_Statistics.html" which is part of the linked ZIP-folder.
- Please be aware that the materials will be updated shortly before the next course.
Dates and Application:
- Courses provided for Helmholtz Munich:
- Courses provided for HIDA:
* Links marked with * are only available for Helmholtz Munich staff.