|
HU Credits:
3
Degree/Cycle:
2nd degree (Master)
Responsible Department:
Plantsciences in Agriculture
Semester:
1st Semester
Teaching Languages:
English
Campus:
Rehovot
Course/Module Coordinator:
Dr. Niv DeMalach
Coordinator Office Hours:
By appointment
Teaching Staff:
Dr. Niv DeMalach,
Mr. yuval neumann
Course/Module description:
A course for statistics and visualization in the R environment. R is an open-source software used by most statisticians and researchers from various fields (biology, economy). The advantage of R over all other alternatives is that it contains libraries (packages) for countless specific statistical analyses. Also, R is free software that, in the last decade, has replaced the need to use dozens of specific softwares (each package in R can replace a dedicated feature).
Besides the technical tools, in the course we will learn to simulate artificial data as a means of testing whether the accepted methods succeed in analyzing the data accurately.
Course/Module aims:
The students will be able to use R as a tool for data analysis and visualization. The ability to analyze data using code is an indispensable tool in research and industry.
Learning outcomes - On successful completion of this module, students should be able to:
The students will be able to use R as a tool for data analysis and visualization. The ability to analyze data using code is an indispensable tool in research and industry.
Attendance requirements(%):
none
Teaching arrangement and method of instruction:
Lectures in classroom and exercises in the computer room
Course/Module Content:
1. The R environment
2. Data management
3. Bivariate relationship of continuous data
4. Categorical data
5. Generalized linear models
6. Multiple regression
7. Non-linear relationships
8. PCA
Required Reading:
None
Additional Reading Material:
1. Michael Crawley – Statistics an Introduction using R
2. Joseph Schmuller – Statistical analysis with R For dummies
3. Stephen C. Loftus - Basic Statistics With R
4. Tony Fischetti - Data analysis with R
Grading Scheme :
Essay / Project / Final Assignment / Home Exam / Referat 50 %
Submission assignments during the semester: Exercises / Essays / Audits / Reports / Forum / Simulation / others 40 %
Presentation / Poster Presentation / Lecture 10 %
Additional information:
Limited to 56 participants. Priority for PhD and Master's students
|
