Basic statistical Analysis is an essential skill for medical researchers. In this course, the basic Statistical Principles are discussed as follow:

• Application of probability in medicine
• Elementary laws of probability
• Conditional probability and Bayes' Rule
• Sensitivity, specificity, Positive and negative predictive value of a
• Point and Interval Estimation for population parameters

• Large sample CI for one-sample mean and proportion
• Large sample CI for differences between means and proportions
• Sample size for estimation
• Test of Hypothesis

• The concept of statistical power, P-value and level of significance

• Student's t-test for one-sample and two-sample situations
• ANOVA for one-way tables

• Post Hoc tests and HOV tests
• Sample size for significance and power analysis
• Chi-square test for simple situations

• Linear Regression

• Scatter Plot and coefficient of correlation
• Estimation of parameters for simple linear regression
• Assessing the model with standard error, R-squared, and slope
• Checking model assumptions

• Extend the model to multiple linear regression