Packages for statistical analysis - course description

General information

Course name	Packages for statistical analysis
Course ID	13.2-WF-FizD-PfSA-S17
Faculty	Faculty of Physics and Astronomy
Field of study	Physics
Education profile	academic
Level of studies	Second-cycle studies leading to MS degree
Beginning semester	winter term 2019/2020

Course information

Semester	2
ECTS credits to win	3
Available in specialities	Medical Physics
Course type	obligatory
Teaching language	english
Author of syllabus	dr hab. Jarosław Piskorski, prof. UZ

Classes forms

The class form	Hours per semester (full-time)	Hours per week (full-time)	Hours per semester (part-time)	Hours per week (part-time)	Form of assignment
Laboratory	30	2	-	-	Credit with grade

Aim of the course

The student can use packages for statistical analysis to support biomedical statistical data analysis as well as data visualisation. The student is also able to support less advanced users of statistical packages in their day-to-day work.

Prerequisites

The knowledge of statistical methods, with the special emphasis on biostatistics. Familiarity with Microsoft office, especially the Excel spreadsheat or LibreOffice and Calc. Ability to program using R.

Scope

Overview of statistical packages and trends in their applications

Aims and methods of general purpose statistical packages

Spreadsheet based graphical user interface

Data transformations in a spreadsheet

Elements of Visual Basic for spreadsheets

Data transformations in spreadsheet with Visual Basic

File and format exchange between R and xls and ods with the XLCONNECT library

Excel/Calc graphics vs R graphics

Elements of the SPSS package with GNU PSPP

File and format exchange between SPSS and R with the use of the foreign library

Teaching methods

Laboratory classes. Working in groups, joint solving of more complicated or laborious examples.

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

The condition of positive assessment is the accomplishment of all programming exercises.

Notes

Modified by dr hab. Piotr Lubiński, prof. UZ (last modification: 05-03-2020 15:36)

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