An introduction to statistical methods common in modern experimental research
Artem Belopolskiy
Course Description
Students will learn ins and outs of applying and interpreting statistical techniques that are common or are becoming common in modern experimental research. The topics covered in this course are:
- Basic statistical principles (e.g. research design, data exploration)
- Inference about one and two populations: independent and paired t-tests, nonparameteric difference tests
- Inference about more than two populations: one-way and two-way ANOVA
- Linear regression models: multiple linear regression for one and more populations
- Inference under dependence: repeated measurements and mixed effects models
- Generalized linear models: logistic regression and Poisson regression
Study Characteristics
- Discipline: Human Movement Sciences: Sport, Exercise and Health (Research)
- Type of education: Lectures and computer assignments
- Academic skill: N/A
- Graduate School: N/A
- Start date: TBD
- End date: TBD
- Minimum number of students: N/A
- Maximum number of students: N/A
- Admission criteria: Contact the course coordinator for information on admission criteria: dr. R. Hindriks
- Concluding assessment: N/A
- Assessment type: N/A
- With Certificate: N/A
- Schedule info: N/A
- Number of lessons: N/A
- Total course duration in hrs.: N/A
- Sign up period: N/A
- Anticipated hrs of study: N/A
- Available to: PhD students VU (and VU RMA students)
-
Course Description & Study Characteristics
Course Description
Students will learn ins and outs of applying and interpreting statistical techniques that are common or are becoming common in modern experimental research. The topics covered in this course are:
- Basic statistical principles (e.g. research design, data exploration)
- Inference about one and two populations: independent and paired t-tests, nonparameteric difference tests
- Inference about more than two populations: one-way and two-way ANOVA
- Linear regression models: multiple linear regression for one and more populations
- Inference under dependence: repeated measurements and mixed effects models
- Generalized linear models: logistic regression and Poisson regression
Study Characteristics
- Discipline: Human Movement Sciences: Sport, Exercise and Health (Research)
- Type of education: Lectures and computer assignments
- Academic skill: N/A
- Graduate School: N/A
- Start date: TBD
- End date: TBD
- Minimum number of students: N/A
- Maximum number of students: N/A
- Admission criteria: Contact the course coordinator for information on admission criteria: dr. R. Hindriks
- Concluding assessment: N/A
- Assessment type: N/A
- With Certificate: N/A
- Schedule info: N/A
- Number of lessons: N/A
- Total course duration in hrs.: N/A
- Sign up period: N/A
- Anticipated hrs of study: N/A
- Available to: PhD students VU (and VU RMA students)
Would you like to register or want to know more?
Please contact the course coordinator Artem Belopolskiy