| Course label : | Statistics 1 |
|---|---|
| Teaching departement : | EEA / Electrotechnics - Electronics - Control Systems |
| Teaching manager : | Mister PIERRE-ANTOINE THOUVENIN / Mister PIERRE CHAINAIS |
| Education language : | |
| Potential ects : | 0 |
| Results grid : | |
| Code and label (hp) : | MR_DS_S1_ST1 - Statistics 1 |
Education team
Teachers : Mister PIERRE-ANTOINE THOUVENIN / Mister PIERRE CHAINAIS
External contributors (business, research, secondary education): various temporary teachers
Summary
• Data types and description of the distribution of univariate random variables: probability distribution / density function, cumulative distribution function, quantile functions, moments (mean, variance, skewness, kurtosis) Graphical representations: pie charts, barplots, histograms, boxplots, … • Confidence intervals. • Bivariate statistical analyses: Mean comparisons with t-tests or ANOVA (when one variable is qualitative, the other one quantitative), chi-squared independence tests (when the variables are both qualitative), correlation analysis (when the variables are both quantitative) • Classifiers: introduction to decision theory and ROC curves. The course will be illustrated by many examples on computer, using the R software.
Educational goals
After successfully taking this course, a student should be able to: • use standard statistical exploration tools from descriptive statistics and have a sound approach of data • be aware that assertions should be statistically tested, and be able to provide scientific evidence of what is read from the data
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: Grading scale: (min) 0 – 20 (max)
Passing grade = 10/20
Online resources
1. Mathematical statistics, Vol. 1&2, P.J. Bickel, K.A. Doksum, CRC Press, Chapman and Hall, 2015 2. Introduction to Probability and Statistics Using R by G. Jay Kerns http://ipsur.r-forge.r-project.org/book/ 3. Introduction to R by Andrew Ellis, Boris Mayer https://methodenlehre.github.io/SGSCLM-R-course/
Pedagogy
24 hours, including lectures and exercise sessions Language of instruction is specified in the course offering information in the course and programme directory. English is the default language.
Sequencing / learning methods
| Number of hours - Lectures : | 12 |
|---|---|
| Number of hours - Tutorial : | 12 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 0 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 0 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
None