Keywords
General description
The course covers descriptive statistics and basics of statistical inference.
Learning outcomes
After completing the course the students are familiar with descriptive statistics and measures of association. They understand the basic principles of statistical inference, modeling and testing. The students can recognize the type of problem they are dealing with and choose appropriate methods for analyzing simple data sets. Student is able to perform the analysis with a statistical software. Further, the students can write a report on the results of their analysis.
Contents
- Data collection, designs
- Descriptive and exploratory data analysis
- Estimation, probability, sampling distributions
- Basics of statistical inference: statistical significance testing, confidence intervals
- Sample size and power
- One-sample, two-sample, multiple samples problems
- Different types of outcomes
- Correlation and other measures of association
- Statistical computing in R
Teaching methods
Classroom work max 40 h.
Teaching language
Finnish, EnglishModes of study
- Degree Programme Students
- Other Students
- Open University Students
- Doctoral Students
- Exchange Students
Participation in classroom work AND Exercise(s) AND Assignment
Evaluation
Pass/fail.Study materials
Latest editions of following books:
Altman D. Practical Statistics for Medical Research. Chapman & Hall.
Moore D and Notz W. Statistics: Concepts and Controversies. W.H. Freeman.
Moore D, McGabe G and Craig B. Introduction to the Practice of Statistics. W.H. Freeman.
Scott and Mazhindu. Statistics for Health Care Professionals.
Further information
The course will be given in English every other year (Autumn 2015 and 2017), and in Finnish every other year (Autumn 2016, 2018).
Belongs to following study modules
2018–2019
