INEB
INEB
Module 1: Introduction to applied statistics with R

The course “Introduction to applied statistics with R” is the first of a set of modules in the area of applied statistics to the life sciences, such as Regression Methods; Analysis of Variance; Analysis of Categorical Data; Mixed effect models (clustered, repeated-measures and longitudinal data). Presenting the certificate of one of the previous modules will guarantee reduced fees.

Dates: 2-3 June 2017 

Course outline:
This short course provides an introduction to basic concepts of statistical methods and data analysis with R applied to life science. The course covers the following topics:

• Introduction to R software
• An overview of statistics. Data description: measurement scales, adequate graphic display
• Summarizing data: measures of central tendency and variability
• Differentiation between population and sample. How to use a statistic to estimate a population’s parameter,
• Confidence interval and its interpretation
• Hypothesis testing: how to set up Null and Alternative hypotheses, understanding Type I and Type II errors
• Comparing two population means, proportions or variances: independent data versus paired data
• Identifying relationships between two variables: categorical variables (chi-square test of independence); quantitative variables (correlation and linear regression)
• Linear regression foundations: least squares method, inferences about the parameters
• Introduction to analysis of variance (ANOVA) methods

 

Course organizers / Responsible lecturer
i3S Statistical Support Team / Carla Maria Oliveira (i3S/INEB)

Software: This course uses R and RStudio (free statistical software)

Location: i3S - Instituto de Investigação e Inovação em Saúde 

Schedule:
9h30-13:00 and 14h00-17h30

Limited registration: 25 participants

Language: Portuguese

Course fees:
i3S staff and students – 70 €  | External (Non-i3S staff) – 90€

Registration deadline: May 30th

 

Registration form >>

Required material: Portable computer with software R (https://cran.r-project.org/) and RStudio (https://www.rstudio.com/) installed