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University of Patras
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Biostatistics

Semester 5th ()

Hours Teaching 2 hours, Laboratory 2 hours, Tutorial 0 hours , Clinical Training 0 hours (per week)

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Description

Purpose
 
Aim of this course is to create the basic statistical sublayer for the comprehension of quantitative estimates and analytic methodologies that are being used in medical science.
  
Methodology
 
The course is taught via lectures (in Amphitheatre) and tutorials in small teams (with use of PC). The lectures have theoretical character and the presented concepts are specified through Tutorials.
 
 
In tutorials are being used:
  • software for statistical analysis of medical and biological data (SPSS, Microsoft Excel, Graph Pad Prism),
  • web pages with relative data and methodologies from the Internet
  • the course in the form of cases STEPS
 
The successful completion of “Biostatistics” includes:
  • the attendance of 2-hour lectures of theoretical character per week
  • the obligatory 2-hour per week attendance of the tutorials with practical exercise in PC,
  • the obligatory participation in in a 10-member team of students in order to prepare a report throughout the course syllabus
  • the success in the oral examination at the presentation of the above report
  • the success in the written examination of the course

Reading Material

​Introduction to Biostatistics

The purpose of Biostatistics - Content of descriptive statistics and statistical inference - Basic concepts of statistics.

Descriptive statistics

Frequency and cumulative frequency-Qualitative results of statistical tests - Quantitative results of statistical experiments - Random variable - frequency tables - Histograms - Representative values of frequency distribution - Sources of sampling variance and determination of the total standard deviation of the sample - Interpretation of the dispersion of clinical measurements.

Theory of probabilities

Definition of probability - Calculation of probabilities - the predictive value of the diagnostic test – Bayes Theorem - Medical applications - Generalization of the Bayes Theorem - Definition of random variable - probabilities distribution of random experimental potential - Characteristic parameters of probability distributions - probabilities distribution in Health Sciences - Binomial distribution - Poisson distribution - Normal distribution (distribution Gauss) – Approach of the binomial distribution via the normal distribution - Approach of the Poisson distribution via the normal distribution.

Statistical sampling

Distribution of medians - Standard Error  of the average sampling data - Central Limit Theorem - sampling error rate - sampling error of the difference between two random variables.

Methods of statistical inference

Point estimation - Determination of the statistical parameters’ confidence interval - Testing statistical hypotheses - Statistical test of the mean - Statistical comparison of the mean values of two different samples - Types of errors in statistical inference - The validity of the statistical test and its relationship with the sample size - Statistical analysis of percentages - Inference for a sample rate - Inference for two sampling rates - Contingency tables and statistical tests based on the x2 distribution - Applications of x2 distribution with degrees of freedom more than one - Subdivision of contingency tables - Statistical comparison of two numbers.

Statistical dependence and correlation

Conceptual difference between dependence and correlation - Least squares method - Use of straight lines of statistical dependence in the clinical forecast - Confidence interval of straight line - Linear factor of correlation.

Tutorials

  • Tutorial 1: Calculation of frequencies, relative frequencies, cumulative frequencies, creation of histograms, criteria of appropriateness of histograms.
  • Tutorial 2: Application of Bayes Theorem, calculations of positive & negative predictive value, transport of data from the Internet in software of statistical analysis, confirmation by calculation of independence of complex possibilities.
  • Tutorial 3: Solving binomial experiment for infinite and finite number of tests
  • Tutorial 4: Simulation of experiments and confirmation of Central Limit Theorem, use of statistical z tables.
  • Tutorial 5 and 6: Solving exercises with use of z test and  t test, error analysis type I and II
  • Tutorial 7: Contingency tables, x2 test
  • Tutorial 8: Solving  exercises of linear regression, finding the 95% confidence interval of the regression line
  • Tutorial 9: Calculation of the linear correlation coefficient in biological and medical Internet data
  • Tutorial 10 and 11: Finding the ROC curve (Receiver's Operating Characteristic curve) and analysis