This lecture consists of 2 parts:

Part 1:
Explains the meaning of relative risk (RR), odds ratio (OR) and hazard ratio (HR) in correlation to studying the confidence interval.

Part 2 :
Introduction to SPSS program is given explaining the import and entry of data.

Part 1:
All information of the previous lectures is summarized in a simple algorithm.

Part 2:
An introduction to SPSS program is given explaining the data transformation.

This lecture is containing 2 parts:

Part 1:
It explains the methods of presentation of univariable statistics which include one dependent and no independent variables. The lecture explains how to present normally distributed (symmetric continuous variables by mean ± SD, how to present non-normally distributed (asymmetric) continuous variables by median & range and how to present ordinal variables by median & range, as well as presenting nominal variables whether affected by time through calculation of the rate or not affected by time through calculation of proportion and percentage.

Part 2:
Practical applications on the calculation of mean, standard deviation, median and different types of presentation of the range including interquartile range.

This lecture consists of 2 parts:

Part 1:
Includes explanation of the basic principles of the types of statistical tests used for bivariable analysis which compares between one dependent variable and one independent variable such as student’s t-test, Mann–Whitney test and Pearson correlation coefficient.

Part 2:
Practical applications of the previously mentioned statistical tests.

This lecture consists of 2 parts:

Part 1:
Continuation of explanation of the basic principles of different tests of bivariable analysis including Spearman rho, Chi-square and Fisher’s exact tests.

Part 2:
Practical applications of the previously mentioned tests.

This lecture consists of 2 parts:

Part 1:
Explains the basic principles of the types of statistical tests used in multivariable analysis which are used for comparison between one dependent variable with 2 or more independent variables. Examples of these tests include analysis of variance (ANOVA) test, Kruskal-Wallis test, and logistic regression analysis.

Part 2:
Practical applications of the previously mentioned tests.

This lecture consists of 2 parts:

Part 1:
Includes continuation of explanation of the basic principles of the multivariable analysis including Kaplan Meier curve, Long-rank test and Cox regression.

Part 2:
Practical applications of the previously mentioned tests..

In this lecture, there are explanation of the methods of assessment of the diagnostic performance of a new test including sensitivity, specificity, diagnostic accuracy, positive predictive value, and negative predictive value.
Moreover, the calculation of the cut-off values by using the Receiver Operator Characteristic (ROC) curve is explained with explanation of the meaning of the area under the curve (AUC).

This lecture consists of 2 parts:

Part 1:
In this lecture, the types of statistical errors (Type I and Type II) are explained. In addition to that, the meaning and the difference between statistical significance and clinical importance are clarified. Following these, the formulae of calculation of the sample size in different types of medical studies whether observational or interventional are illustrated.

Part 2:

• Practical applications through using G* power program (mean difference and proportion difference) are given.
• This part also explains the interpretation of the results of a meta-analysis.
  Lectures of this sector are followed by multiple choice questions and their answers to consolidate the information mentioned in every lecture.