## Biostatistics

**Semester** 5th ()

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

**Teachers**

### Description

**Purpose**

**Methodology**

- 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 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