Statistical Computer Analysis - course description

General information

Course name	Statistical Computer Analysis
Course ID	14.2-WP-SOCDA-KAS
Faculty	Faculty of Social Sciences
Field of study	Sociology
Education profile	academic
Level of studies	Second-cycle studies leading to MS degree
Beginning semester	winter term 2022/2023

Course information

Semester	2
ECTS credits to win	4
Course type	obligatory
Teaching language	english
Author of syllabus	dr hab. Dorota Szaban, prof. UZ dr Tomasz Kołodziej

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

Preparing students for the application of basic procedures for the analysis of survey data and their practical use: calculating, analyzing and interpreting the results of empirical research. Acquisition by students of the ability to use the IBM Statistics SPSS statistical package.

Prerequisites

Scope

1. Creation and management of data sets.

2. Data operations, the use of basic statistical measures. Create new variables.

3. Create indexes. Reliability analysis

4. Multivariate analysis - correlations, factor analysis, linear regression.

Teaching methods

Working with a computer program, e-learning, blended learning

Learning outcomes and methods of theirs verification

Outcome description	Outcome symbols	Methods of verification	The class form

Assignment conditions

Passing of three tests and implementation of the tasks provided for in the program

Notes

Students may receive a licensed version of the IBM statistics SPSS program (in the new version of each year) licensed as part of the Ariadna program for use in the implementation of their own projects.

Modified by dr Tomasz Kołodziej (last modification: 30-04-2022 19:59)

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