Computer Data Analysis in Healthcare Practice

Adatok

A Tantárgybejelentőben megadott hivatalos adatok az alábbi tanévre: 2025-2026

Tematika

This optional course provides students with fundamental knowledge essential for preparing lab reports, particularly during their internships. The course focuses on the practical use of spreadsheet applications, primarily Microsoft Excel, covering everything from basic operations to the implementation of mathematical and statistical functions. The skills acquired in this course will be valuable not only during their studies but also in future careers, whether in research, medical and pharmaceutical practice, or as PhD students.

Előadások

• 1.

  Introduction: Matrix-based data systems I. Basics of spreadsheets and Microsoft Excel. Data entry, structure, and formatting. Keyboard shortcuts.

  - Vékony Roland Gábor
• 2.

  Introduction: Matrix-based data systems II. Basics of spreadsheets and Microsoft Excel. Data entry, structure, and formatting. Keyboard shortcuts.

  - Vékony Roland Gábor
• 3.

  Charts I. Types of graphs and selection criteria. Diagram characteristics.

  - Vékony Roland Gábor
• 4.

  Charts II. Scaling, data labels, and formatting. Dual-axis and mixed chart types.

  - Vékony Roland Gábor
• 5.

  Formulas and Functions I. Data analysis models and data grouping.

  - Trombitás Norbert
• 6.

  Formulas and Functions II. Data analysis models and data grouping.

  - Trombitás Norbert
• 7.

  Regression and Fitting I. Linear regression.

  - Bukovics Péter
• 8.

  Regression and Fitting II. Exponential regression.

  - Bukovics Péter
• 9.

  Regression and Fitting III. Logistic regression.

  - Trombitás Norbert
• 10.

  Macros and additional Excel features.

  - Trombitás Norbert
• 11.

  Useful Excel tips and tricks. Summary of key concepts.

  - Bukovics Péter
• 12.

  Student project presentations.

  - Bukovics Péter

Gyakorlatok

Szemináriumok

A tananyag elsajátításához szükséges segédanyagok

Kötelező irodalom

Saját oktatási anyag

LinkedIn: Learning Excel;

Microsoft Press: Data Analysis Fundamentals with Excel;

Udemy: Learn The 10 Most Powerful Microsoft Excel Tips and Tricks;

Udemy: Microsoft Excel - Excel from Beginner to Advanced.

Jegyzet

The course is delivered in a block format, held biweekly: one session consisting of two 45-minute lectures (a total of 90 minutes), during which the practical elements are followed by the students on computers.

Ajánlott irodalom

Excel Formulas and Functions for Dummies (3rd Edition)

Statistical Analysis with Excel for Dummies

A félév elfogadásának feltételei

At the end of the semester, students are required to present a previously prepared project during the final week of the course at the scheduled time. Successful completion of the course will result in a recommended exam grade.

Félévközi ellenőrzések

Optional homework assignments can be completed during the semester. Successfully completing these may exempt students from the end-of-semester exam task.

Távolmaradás pótlásának lehetőségei

If multiple groups are running, students may attend another group’s session. In the case of multiple absences affecting several students, one extraordinary (extra-curricular) make-up class may be scheduled per semester in consultation with the students.

Vizsgakérdések

1. Introduction: Overview of matrix-based data management systems and spreadsheets. Understanding Microsoft Excel and its versions. Basics of Excel: concepts, handling, and filtering of cells, rows, and columns.

2. Data Entry and Modification: Data collection, modification, and cell data types. Combining and transforming data. Cell styles and formatting. Importing data. Understanding data structures in Excel. Formatting options, including keyboard shortcuts and insert functions.

3. Charts and Graphs: Types of charts and their applications. Selecting the appropriate chart type based on the purpose of analysis.

4. Chart Customization: Representation modes, scaling, and data labels. Formatting charts, including biaxial and mixed representations.

5. Formulas and Functions: Understanding formulas, their operation, and arguments. Function compatibility. Introduction to essential functions. Dynamic data handling. Referencing workbooks, worksheets, and functions. Managing errors in functions and handling intersection points.

6. Data Analysis and Modeling: Ensuring data integrity. Identifying required data structures and functions. Grouping data within a model.

7. Regression Analysis – Linear Regression: Understanding and applying linear regression in Excel. Linear trend lines. Using the equation of a line for analysis. Practical examples and visualization.

8. Exponential Regression: Understanding and applying exponential regression in Excel. Practical examples and visualization.

9. Logistic Regression: Understanding and applying logistic regression in Excel. Practical examples and visualization.

10. Automating Repetitive Tasks – Macros: Introduction to macros, adding and editing macros, and creating useful automated tasks. Exploring additional Excel features. Understanding links, sheet protection, and workbook security.

Vizsgáztatók

Gyakorlatok, szemináriumok oktatói