Course will cover descriptive statistics, population and sample, parameters estimation, testing statistical hypotheses for one and two populations, chi-square test of independence, analysis of variance, correlation and regression.
The main objective of the course is to give a sound and self-contained description of classical or mainstream statistical applications.
Students will learn how to carry out simple and advanced analysis of data. They will understand the differences between population and sample. Students should understand probability and random events. The students should have a clear understanding of random variable and its distribution.
The students should learn to formulate and solve basic problems of statistics, such as parameters estimation, statistical hypotheses testing, correlation analysis, analysis of variance, Spearman correlation, contingency tables and regression analysis. One of the course objectives is to prepare students for further studying simple and multiple regression models.
Give a sound and self-contained statistical applications
Learn how to carry out simple and advanced analysis of data
Understand the differences between population and sample
Understand probability and random events
Have a clear understanding of random variable and its distribution
Solve basic problems like parameters estimation, statistical hypotheses testing and ANOVA
Fundamantals of Biostatistics. 8th Ed. By Bernard Rosner.
Biostatistics: A foundation For Analysis in the Health Sciences. 5th Ed. By Wayne W. Daniel.
Sampling Methods for Applied Research. Text and Cases. By Peter Tryfos.
Methods in Biostatistics With Latest MCQs. By K. S. Negi.
Activity | Percent (%) |
---|---|
Assignments | 20% |
Projects | 20% |
Exams | 60% |