Course title in Estonian
Andmeanalüüs: statistiline andmestik ja kirjeldav statistika
Course title in English
Data Analysis: Descriptive Statistics
approximate amount of contact lessons
autumn - spring
lecturer of 2019/2020 Autumn semester
lecturer not assigned
lecturer of 2019/2020 Spring semester
lecturer not assigned
To create opportunities for acquiring theoretical knowledge and practical skills for processing statistical data and caring out elementary data analysis with the aid of SPSS software. The course is also set up to support developing ones ability to chose appropriate methods for analysis and presentation, as well as to understand and interpret correctly the meaning of statistical results.
Brief description of the course
Classification and main features of research approaches and methods. Basics of the data collection. Statistical data and preparation for analysis. Different types of data. Descriptive statistics: frequency and summary tables, statistics and charts. Relationships: measures of association and cross-tables. Course consists of seminars where students are expected to be actively involved.
Every student must submit home assignment, which consists of three parts and covers all methodological aspects of the research project.
Learning outcomes in the course
Recognises and can comparatively differentiate between different types of research designs;
Knows what are the main quality criteria for academic research;
Can design simple instruments for data collection;
Can create statistical data-table with an appropriate structure;
Has got experience in setting up questions about data which lead to statistical analysis; Understands main concepts of descriptive statistics, knows the prerequisites for their correct application and can interpret the results of the analysis correctly;
Can recognise different types of variables and choose appropriate statistical techniques accordingly;
Can use the statistical software with the aid of the manual for simple data processing and analysis.
The assessment grade is based on two parts:
1) the written test will be assessed on a scale of
"A" - excellent 91-100%
"B" - very good 81 - 90%
"C" - good 71 - 80%
"D" - satisfactory 61-70%
"E" - sufficient 51 - 60%
"F" - fail 0-50%
2) home assignment will be assessed on a scale
"+" - a very good job (the test score increases by one grade),
"0" - good work (leaves the test score change)
"-" - decent work (take a test score by one grade)
"F" - fail (the work isn’t reported or the unsatisfactory and should be re-submitted)
Keeping score for a positive outcome it is necessary that both works are done (written test, home assignment).
Kairi Osula, Triinu Jesmin, Jaanika Meigas
The course is a prerequisite
Niglas, K. Statistika loengumaterjale http://www.tlu.ee/~katrin/ ;
Niglas, K. 2007 Andmeanalüüs statistikapaketi SPSS 14.00 abil. Põhikursus.
Soovitav on omada eelteadmisi kontoritarkvara kasutamisest ja tabelarvutusest.
Hiob, K. 1995 Matemaatiline statistika. Algkursus koolidele;
Tooding, L.- M. 1999 Andmeanalüüs sotsiaalteadustes;
Tooding, L. M. 2007 Andmete analüüs ja tõlgendamine sotsiaalteadustes;
Hirsijärvi, S., Remes,P., Sajavaara, P. 2005 Uuri ja kirjuta;
Ghauri, P. 2004 Äriuuringute metoodika;
Kidron, A. Uurija käsiraamat.