Biostatistics Course: Statistical Analysis applied to Research Data
Biostatistics Course: Statistical Analysis applied to Research Data
The course will give an overview of important concepts and methods used to analyse “Biomedical data”. The emphasis will be on the understanding of statistical concepts and their interpretation in a research framework. After a general introduction on probability theory and statistical inference, an emphasis will be made on common statistical methods. Particular cases will be used as illustrative examples.
The course will be composed of face-to-face theoretical lectures combined with practical sessions and additional short homework assignment (approx. 1 h per week).
Teacher: Hafid Laayouni (UPF)
Duration: 10 sessions (total 20h; 14h theory + 6 h practicals)
Schedule: 20th April- 22nd June, Fridays 10:00- 12:00
Maximum nº students: 20
Requirements: Participants need to have a basic R programing skills
Application deadline: 24th of March 2018
|
Session |
Type |
Title |
Date (Fridays) |
Hour |
Room |
|
T01 |
Theory |
Introduction. Descriptive statistics. Probability and distributions. Sampling distribution. Confidence intervals |
20th April |
10-12 |
Aula room |
|
T02 |
Theory |
Hypothesis testing. The t-test. |
27th April |
10-12 |
Aula room |
|
P01 |
Practicum |
Exercises and Hands on sessions 1-2. |
4th May |
10-12 |
Bioinformatics room |
|
T03 |
Theory |
Analysis of variance. One-way ANOVA |
11th May |
10-12 |
Denmark |
|
T04 |
Theory |
ANOVA. Multiple comparison procedures. Two-way ANOVA. |
18th May |
10-12 |
Aula Room |
|
P02 |
Practicum |
Hands on sessions 3-4. |
25th May |
10-12 |
Bioinformatics room |
|
T05 |
Theory |
Correlation and regression |
1st June |
10-12 |
Aula room |
|
T06 |
Theory |
Multiple regression analysis. Partial correlation. |
8st June |
10-12 |
Bioinformatics room |
|
P03 |
Practicum |
Hands on sessions 7-8 |
15st June |
10-12 |
Bioinformatics room |
|
T07 |
Theory |
Analysis of Covariance. Effect Size, and a summary of inference methods. |
22st June |
10-12 |
Aula room |
At the end of the course, the students will be able to:
- Express a scientific question in a mathematical formulation possible to analyse with statistical method.
- To be confident about sampling methods and their impact on the quality of the data.
- Think on the basis of experimental design: replication, randomization and stratification.
- Think about the appropriate statistical method given the data we have (dependent and/or independent variable, continuous or categorical variables).
- Have a deep understanding of the meaning and interpretation of a test statistic and how to construct own statistic given data.
- Have a correct understanding of key words in basic statistic: null hypothesis, alternative hypothesis, error type I, error type II, statistical power, observational study, experimental study, causation and correlation, sampling error, random error, systematic error, sampling distribution, p-value, statistical and practical significance, effect size, statistical power.
- Correct interpretation of the result of a statistical test and been aware of the limitations of the applied methods.
