BFZ610 Advanced Data analysis in Biophysics (Z)

7 ECTS - 2-2 Duration (T+A)- . Semester- 3 National Credit

Information

Code BFZ610
Name Advanced Data analysis in Biophysics (Z)
Semester . Semester
Duration (T+A) 2-2 (T-A) (17 Week)
ECTS 7 ECTS
National Credit 3 National Credit
Teaching Language Türkçe
Level Doktora Dersi
Type Normal
Mode of study Yüz Yüze Öğretim
Catalog Information Coordinator Prof.Dr. İSMAİL GÜNAY


Course Goal

To teach the classification of numerical data obtained from the measurements made, to comprehend the graphic drawings by using the statistical program to be applied.

Course Content

Measurements in biophysics, nerve conduction velocity, nerve action potential, muscle contraction, muscle relaxation, reflex tests, molecular measurements, graphic programs, statistical programs

Course Precondition

Resources

Lecture notes (For Medical Faculty Students - İsmail Günay) Biophysics (Ferit Pehlivan) Biophysics (Gürbüz Çelebi) Internet Search

Notes

Internet Research


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Learns the devices used in measurements
LO02 Measures the numerical data measured from the devices used with its units.
LO03 Categorizes the numerical data measured from the devices
LO04 Learns the computer programs to use
LO05 Learns the statistical program to be applied to the received numerical data.
LO06 numerical data is evaluated statistically
LO07 Draws graphs according to statistical data.


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal To learn the basic information about the field 5
PLO02 Bilgi - Kuramsal, Olgusal To be able to establish experimental work in laboratory 5
PLO03 Bilgi - Kuramsal, Olgusal To prepare a project proposal by itself 5
PLO04 Bilgi - Kuramsal, Olgusal To plan an experimental research 5
PLO05 Bilgi - Kuramsal, Olgusal To make a report as a result of the research 5
PLO06 Bilgi - Kuramsal, Olgusal To be able to interpret research findings 5
PLO07 Bilgi - Kuramsal, Olgusal Having analytical thinking mechanism related to the field Accessing reliable information Creating and writing a research project Study and research based on ethic values 5
PLO08 Bilgi - Kuramsal, Olgusal Ability to transfer the theoretical knowledge to the audience in a systematic way 5
PLO09 Bilgi - Kuramsal, Olgusal To have scientific thought systematic about the profession 5
PLO10 Bilgi - Kuramsal, Olgusal Kendi başına bir proje önerisi hazırlayabilmek 5


Week Plan

Week Topic Preparation Methods
1 What is measurement?What are the measurement errors? Student reads the related section before class Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Devices used in biophysics Student reads the related section before class Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Alıştırma ve Uygulama
3 Numerical data received from devices Student reads the related section before class Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
4 Ölçülen verilerin sınıflandırılması Student reads the related section before class
5 Recording of digital data in computer environment Student reads the related section before class
6 Computer Programs Used Student reads the related section before class
7 Statistics programs Student reads the related section before class
8 Mid-Term Exam Ölçme Yöntemleri:
Yazılı Sınav, Ödev, Performans Değerlendirmesi
9 Which statistical program should be used for which data? Student reads the related section before class
10 Graphics Programs Student reads the related section before class
11 Entering given to SP Program Student reads the related section before class
12 graphic drawing Student reads the related section before class
13 Evaluation of sample statistical data Student reads the related section before class
14 Evaluation of graphics with SP Student reads the related section before class
15 Analysis of data evaluated statistically Student reads the related section before class
16 Term Exams Ölçme Yöntemleri:
Yazılı Sınav, Ödev, Performans Değerlendirmesi
17 Term Exams Ölçme Yöntemleri:
Yazılı Sınav, Ödev, Performans Değerlendirmesi


Student Workload - ECTS

Works Number Time (Hour) Workload (Hour)
Course Related Works
Class Time (Exam weeks are excluded) 14 4 56
Out of Class Study (Preliminary Work, Practice) 14 6 84
Assesment Related Works
Homeworks, Projects, Others 1 9 9
Mid-term Exams (Written, Oral, etc.) 1 8 8
Final Exam 1 16 16
Total Workload (Hour) 173
Total Workload / 25 (h) 6,92
ECTS 7 ECTS