Title  ΙΑΤΡΙΚΗ ΣΤΑΤΙΣΤΙΚΗ / Medical Statistics 
Code  ΙΑ0278 
Faculty  Health Sciences 
School  Medicine 
Cycle / Level  1st / Undergraduate 
Teaching Period  Winter 
Coordinator  AnnaBettina Haidich 
Common  No 
Status  Active 
Course ID  200000276 
Programme of Study: UPS of School of Medicine (20142015)
Registered students: 341
Orientation  Attendance Type  Semester  Year  ECTS 

Core  Core Courses  1  1  2.5 
Academic Year  2017 – 2018 
Class Period  Winter 
Faculty Instructors 

Weekly Hours  3 
Class ID  600106153

Section  Instructors 

1. ΕΡΓΑΣΤΗΡΙΟ ΥΓΙΕΙΝΗΣ, ΚΟΙΝΩΝΙΚΗΣΠΡΟΛΗΠΤΙΚΗΣ ΙΑΤΡΙΚ 
Class Schedule
Building  Ιατρικής (αμφιθέατρο) 
Floor  Όροφος 1 
Hall  ΑΜΦΙΘΕΑΤΡΟ Α (72) 
Calendar  Τετάρτη 08:00 έως 12:00 
Type of the Course
 Background
 General Knowledge
Course Category
General Foundation
Mode of Delivery
 Face to face
Digital Course Content
 eStudy Guide https://qa.auth.gr/en/class/1/600106153
Language of Instruction
 Greek (Instruction, Examination)
Learning Outcomes
For each lecture the objectives are described below:
1 Description, presentation and summary data
• Identification of qualitative and quantitative variables and different types of data
• Presentation and summary data in an appropriate way
• Calculation and interpretation of graphs
• Understand the characteristics of the normal distribution of their difference from the asymmetric distributions
2 Measures of central location and dispersion
• Calculation of measures of central location and dispersion
• Understand the use of appropriate measures of central location and dispersion for summarizing data with normal and skewed distribution
• Description and interpretation of results of measures of central location and dispersion
3 Populations and samples
• Understand the differences in measurements between the population and sample
• Different types of selecting a random sample from a population
• Understand the types of random sampling and their application
• Assessment of the accuracy and repeatability of sampling
• Identify the disadvantages of nonrandom samples
4 Normal distribution
• Identification of the properties of a normal distribution
• Transformation of a normal distribution to a standard normal distribution
• Calculation of various probabilities based on standard distribution
• Find critical values from the table of normal distribution
• Understand the properties of the sampling distribution
• Estimate the difference between the standard deviation and standard error of the mean
5 Hypothesis testing
• Formulate the null and alternative hypothesis
• Understand the concept of Pvalue, the level of significance and the corresponding critical value
• Testing and assessing the significant difference
• Separation between onesided and twosided tests
• Understand type I and II errors and when the power of a study increases
6 Parametric tests of one sample
• Understand application Z and t test
• Formulate the null and alternative hypothesis in the case of a control sample
• Calculation of the Z and t test
• Read and find critical values of the t distribution table
• Interpretation of the results of the test
• Calculation of confidence intervals
7 Parametric tests of two samples
• Understand the difference between independent and dependent samples
• Formulate the null and alternative hypothesis in hypothesis testing between two independent or dependent samples
• Calculation of the t test for two independent or dependent samples
• Interpretation of the results of the tests
• Calculation of confidence intervals
8 Analysis of variance
• Formulate the null and alternative hypothesis in hypothesis testing between three or more independent samples
• Understand the problem of multiple comparisons and how to correct it
• Understand the calculation of the Fratio
• Read and find critical values from Fdistribution table
• Configuring the analysis of variance table
• Procedures for correcting multiple comparisons
9 Correlation between continuous variables
• Understand the importance of the correlation coefficient
• Assessment of the application of different correlation coefficients depending on the types of data
• Calculation of the Pearson correlation coefficient
• Calculation of nonparametric Pearson correlation coefficient
10 Association of qualitative variables
• Understand the application of the chisquare criterion
• Calculation of the goodness of fit test with equal and proportionate number of expected frequencies
• Calculation of the chisquare test for independency and interpretation of results
• Configuring the contingency table
• Calculation of the chisquare test for fourfold (2x2)
• Calculation of the Z test for comparing two proportions in a fourfold table
• Implementation of the Mc Nemar test for dependent samples
11 Nonparametric tests
• Understand the utility of nonparametric tests
• Recognition of the parametric test applied to the relevant comparison
• Application of the MannWhitney test to compare two independent samples
• Implementation of the Wilcoxon test for comparing two dependent samples
• Implementation of the KruskalWallis test for comparison of three independent samples and above
• Assessment of the advantages and disadvantages of nonparametric tests
12 Diagnostic testing
• Calculation and interpretation of sensitivity, specificity, predictive value of positive and negative results
• Understand the restrictions on the use of positive and negative predictive values
• Interpretation of ROC curve
13 Survival analysis
• Decision on data in which the survival analysis is applied
• Understand the concept of censored data
• Calculation and interpretation of life tables
• Interpretation of KaplanMeier curves
• A comparison of two survival curves by Log rank test
• Assessment of the assumptions that must be met to implement the Logrank test
General Competences
 Apply knowledge in practice
 Retrieve, analyse and synthesise data and information, with the use of necessary technologies
 Make decisions
Course Content (Syllabus)
Lecture
1 Description, presentation and summary data
2 Measures of central location and dispersion
3 Populations and samples
4 Normal distribution
5 Hypothesis testing
6 Parametric tests of one sample
7 Parametric tests of two samples
8 Analysis of variance
9 Association between two continuous variables
10 Association of qualitative variables
11 Non parametric tests
12 Diagnostic testing
13 Survival analysis
Keywords
Medical Statistics, Biostatistics
Use of Information and Communication Technologies
Use of ICT
 Use of ICT in Course Teaching
 Use of ICT in Laboratory Teaching
 Use of ICT in Communication with Students
Course Organization
Activities  Workload  ECTS  Individual  Teamwork  Erasmus 

Lectures  39  1.5  ✓  
Tutorial  26  1  
Total  65  2.5 
Student Assessment
Student Assessment methods
 Written Exam with Multiple Choice Questions (Summative)
 Written Exam with Short Answer Questions (Summative)
Bibliography
Course Bibliography (Eudoxus)
Ιατρική Στατιστική: Βασικές αρχές. ΑρβανιτίδουΒαγιωνά Μ,Χάιδιτς ΑΜ. Εκδόσεις University Studio Press, Θεσσαλονίκη 2013.
Last Update
11102016