Python For Biostatistics

The course consists of two parts. In the first part, there are brief explanations of the tests frequently applied in biostatistics. (What is biostatistics and why we use biostatistics?, The order to follow in a research, Mean and faults, Standard Deviation, Standard Error and Coefficient Of Variation, Correlation and Regression, Chi-squared test, T-test, F-test and Multiple Comparison Tests(Tukey, Newman-Keuls, LSD, Duncan and Dunnett))If you know the uses of the tests and the theoretical knowledge of the tests, you do not need to follow them. The second part of the course involves applying the tests on the questions. In the second part of the course, standard deviation calculation, standard error calculation, coefficient of variation calculation, correlation calculation(Calculation of the correlation between pupa weight and butterfly wing length), chi-square test calculation(To test for inter-experimental homogeneity), t test calculation(Calculation of the effect of stinging nettle on cholesterol in rabbits) and f test calculation were applied with python software language.The codes written after the lessons have been added to the explanations of the lessons.Python software language coding was done through PyCharm IDE, but you can use any IDE you want. You can run these codes on your own computer. My English and English accent is bad, so subtitles will be added as soon as possible. I’m sorry if I used the wrong definition and words. Good lessons everyone.