IBM SPSS Applied Statistical Data Analysis Training (Advanced)

Online statistical data analysis training will be organized in cooperation with the Oral Diagnosis and Maxillofacial Radiology Association and the e-statistics statistical analysis platform. You can register by logging into the portal at

Regarding the training that will be organized on 13-19 December, the basic information and registration process are as follows.

Training Days: Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, Sunday

Training Hours: Between 19:00-21:30

Required Documents: It will be shared on December 12 via Google drive.

Required Installations: Everyone should have Microsoft Office programs and at least IBMSPSS V20 installed on their computer. Installation files will be shared on Google drive on December 12 for participants who do not install.

Registration Process 1. You must become a member of the system via If you are a member of the system, you can log in to the system by following the "LOG IN TO THE SYSTEM" path. 2. After logging into the system, first click on “Please select the training you want to attend” in the “New Training Request” (use here to place a new order) tab. Then, from the drop-down list under this heading, you must select “MODULE 1: Basic Level Data Analysis, 13-19 December, Oral Diagnosis and Maxillofacial Radiology Society" training.3. After the selection process, you will complete your registration process as a pre-registration with the “Request” button on the right. 4. In the new window that opens, you can finalize your payment either by credit card or by Wire Transfer/EFT from the "Payment" tab.

Educational content:

• General introduction of IBM SPSS,

• Data entry and data conversion processes

• Obtaining descriptive statistics

• Normality tests • Parametric and non-parametric methods

• Simple and Partial correlation

• Chi-square test

• Use of the “Analysis Selection Diagram” that we have developed for the test selection method.

• Tabulation with Excel formulas developed for reporting techniques

• Data visualization

• Article literacy hour

Educational Materials:

• Field-specific lecture notes

• Domain-specific datasets

• Microsoft Word sample report templates

• Analysis Selection Diagram

• Video recordings of all lessons