Kies de Nederlandse taal
Course module: 202000756
Course info
Course module202000756
Credits (ECTS)3
Course typeStudy Unit
Language of instructionEnglish
Contact personJ.A. Wood
Lecturer G.C. Vreman - de Olde
J.A. Wood
Contactperson for the course
J.A. Wood
Academic year2020
Starting block
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
  • Estimate mean, standard deviation and standard error for samples/populations
  • Explain the different types of statistical errors, the difference between accuracy and precision and how error propagates through calculations
  • Compute and understand the meaning of confidence and prediction intervals
  • Explain the meaning behind p-values of significance and perform hypothesis tests
  • Perform linear regressions in a least-squares sense and explain the link to hypothesis testing, matrix form of analysis, etc.
  • Compute inverse errors in calibration curves
  • Compute regression diagnostics for the suitability of a regression (Lack of Fit testing, Goodness of Fit, normal probability of residuals, coefficient of determination, etc.)
  • Explain the difference between confidence intervals and joint confidence regions
  • Perform multiple regression analysis, compute correlation of parameters, be familiar with the case of error in variables and understand the difference between correlation and causation
  • Apply their learned knowledge to analysing nonlinear regression scenarios and how to fit literature data and interpret the meaning of the resulting fit and parameters
The course ‘Introduction to Statistics’ is a follow up on the statistics you learned during the practicals and will prepare you for the statistics you use in the first courses in your master (both tracks) and throughout your career. Important topics that will be covered include: population and sample statistics, propagation of errors, hypothesis testing and analysis of variance, linear regression, regression diagnostics, multiple regression analysis, transformation of experimental data and nonlinear regression. Emphasis is placed on practical implementation in MATLAB.
Module 11
Participating study
Bachelor Chemical Science & Engineering
Required materials
Applied Statistics and Probability for Engineers by Montgomery and Runger, 7th edition (2014), ISBN13: 9781119585596
Recommended materials
Instructional modes
Presence dutyYes

Presence dutyYes


Kies de Nederlandse taal