1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES
  3. BIOLOGY DEPARTMENT
  4. 1461 Biology
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
Print

COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
BIO 660DATA ANALYSIS AND VISUALIZATION IN ECOLOGY3 + 01st Semester7,5

COURSE DESCRIPTION
Course Level Master's Degree
Course Type Elective
Course Objective The aim is to teach researchers the basic concepts, skills, and tools for working with the data they have obtained and to make the outputs of the data understandable using up-to-date software and techniques.
Course Content Converting data obtained from several studies such as laboratory and field studies by using R statistical software into processable data sets and applying data science techniques; the processing of libraries and visualization techniques used in data analysis methods; transferring outputs to digital document platforms such as Markdown, Knitr, Latex etc.
Prerequisites No the prerequisite of lesson.
Corequisite No the corequisite of lesson.
Mode of Delivery Face to Face

COURSE LEARNING OUTCOMES
1Learns the basic concepts about data.
2Installing the R statistics program and run it on the desired operating system.
3Learns to prepare a data set of species and environmental findings.
4Learns the spatial analysis of ecological data.
5Learns data placement and mapping options.
6Learns univariate, bivariate and multivariate graphic methods.
7Learns time dependent graphing techniques.

COURSE'S CONTRIBUTION TO PROGRAM
PO 01PO 02PO 03PO 04PO 05PO 06PO 07PO 08PO 09PO 10PO 11
LO 001           
LO 002           
LO 003           
LO 004           
LO 005           
LO 006           
LO 007           
Sub Total           
Contribution00000000000

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)129108
Mid-terms11919
Final examination12626
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Spring1GÜRÇAY KIVANÇ AKYILDIZ
Details 2022-2023 Spring1GÜRÇAY KIVANÇ AKYILDIZ
Details 2021-2022 Spring1GÜRÇAY KIVANÇ AKYILDIZ


Print

Course Details
Course Code Course Title L+P Hour Course Code Language Of Instruction Course Semester
BIO 660 DATA ANALYSIS AND VISUALIZATION IN ECOLOGY 3 + 0 1 Turkish 2023-2024 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Asts. Prof. Dr. GÜRÇAY KIVANÇ AKYILDIZ gkakyildiz@pau.edu.tr FEN B0311 %
Goals The aim is to teach researchers the basic concepts, skills, and tools for working with the data they have obtained and to make the outputs of the data understandable using up-to-date software and techniques.
Content Converting data obtained from several studies such as laboratory and field studies by using R statistical software into processable data sets and applying data science techniques; the processing of libraries and visualization techniques used in data analysis methods; transferring outputs to digital document platforms such as Markdown, Knitr, Latex etc.
Topics
Materials
Materials are not specified.
Resources
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes