Statistical analysis of data is a key step in every scientific experiment. In spite of the presence of many websites devoted to statistical analysis, every science has its own characteristic features and it is much easier to perform statistical evaluation of data using examples with similar situations as guidelines.
The main goal of this website is to describe how to select the appropriate statistical test for assessment of biomedical data, how to apply this test and then how to interpret obtained results. Each step of statistical analysis is illustrated in detail by examples selected from our studies. For statistical methods which are still not very common in biomedical researches, for example, logistic regression, we characterized some selected examples from published studies that may help to find ideas about application of these methods in researches of the reader.
Because the most commonly used statistical software is SPSS®, examples are given in this software package, in its recent version 20. However, since other statistical packages apply the same principles, the examples can be easily performed in similar software, such as SAS, STATISTICA, MedCalc, etc.
The analysis of researcher preferences in the use of different statistical packages is also done, along with the analysis of application of different statistical methods in published microbiological studies (as the main specialization of website author is microbiology), and with short guidelines in the freeware statistical packages.
The site describes consecutive steps in analysis of biomedical data starting from formulating the purpose with expected results and performing descriptive statistics with assessment of data distribution, which are the key steps in selecting criteria for the further analysis. Next pages include the comparison of groups of data, the study of relations between variables, the classification of data and the methods of prognosis. The materials are written maximally close to practical application of statistics with the minimally necessary theoretical preface to each chosen method.
Click on the links below to read about various topics in biomedical statistics: