BIOSTATISTICS

Learning outcomes- EQF Level: 6

The purpose of the course
Τhe course aims to enable students to understand the statistics’ techniques and to become familiar with the statistical science. Additionally, upon the completion of the course of Applied Statistics the students will be able to think in a more efficient way and make better decisions in relation to the uncertainty of the future. Moreover, it will be possible to implement the theory of statistics in P/C lab with the appropriate statistical packages as SPSS.

Learning outcomes
On successful completion of the course the students will have acquired all the basic concepts of statistics that are essential in the field of health sciences. In particular, they will be able to:
• Have basic knowledge about statistics and its application to the description and analysis of data in health science.
• Understand the methods of descriptive statistics and statistical inference in topics of health research and practice. As far as knowledge is concerned, students will know to recollect and describe:

• data collection and analysis
• The use of hypothesis testing
• The estimation of correlation and regression

 

In regard to the skills, students will be able to explain and deduce conclusions regarding:

• data collection and analysis.
• The use of hypothesis testing.
• The estimation of correlation and regression.

 

With reference to competences students will be capable to apply the above as follows:

• By organizing data.
• By understanding basic statistical tools.
• By using statistical techniques for the analysis of real data.

 

SYLLABUS

Theory
The course is designed for a set of 13 weeks of lectures. The topics that will be discussed are the following:

• The role of statistics in health sciences –
• Basic concepts – Choosing the appropriate statistical analysis – Design of a medical research
• Population and Sample – Sampling methods – Size of sample
• Collecting and presenting data
• Statistical Descriptive Measures
• Mean-Variance
• Hypothesis Testing –Confidence Intervals
• Analysis of Variance – Applications
• Non-parametric tests
• Odds Ratio – Relative Risk
• Dependence – Correlation
• Linear Regression – Applications
• Logistic Regression – Applications

 
Lab
The lab sessions take place in a computer lab equipped with all the necessary software. The following sections are covered:

• Descriptive Statistics
• Presenting Data
• Confidence Intervals
• Hypothesis Testing (t-test, independent samples)
• Hypothesis Testing (t-test, dependent samples)
• Hypothesis Testing (proportions)
• Non-parametric procedures (chi-square – Kruscal-Wallis, …)
• Non-parametric procedures (independent samples, Mann-Whitney test, Wilcoxon test, …)
• Analysis of Variance
• Linear Regression
• Logistic Regression
• General Exercises
• Final Exams