Course for international guest/part time students

Faculty

Faculty of Social Sciences

Organization

TÁTK Minority Studies Department

Code

EKIP15.1

Title

Research methods 2

Usual semester

Spring

Published semester

2025/26/2

ECTS

5

Language

en

Learning outcomes

The main goal of the seminar is to introduce quantitative analysis to the students. Moreover, the course will give an insight and practice in data analysis and interpretation of results in ethnic and minority studies.  'Research methods II' will focus on statistical analysis with SPSS.

Course content

Week Topics 1st Introduction to the semester. Recapitulation: research question, operationalization, variables and properties of variables. Introduction to research and datasets will be used during the semester. Readings: Operationalization and properties of variables in Babbie; questionnaires 2nd Introduction to SPSS. Reasons and usage of descriptive statistics. Basic description of a variable: distribution, frequency. Readings: none 3rd Descriptive statistics: central tendency and variability measures. Readings: Social Statistics (Lecture 5-6) 4th Basics of data manipulation: transforming variables, quantiles in practice. Homework: Descriptive statistics and their interpretation for 4 variables (at least one of them high level of measurement and at least one of them low level of measurement. Points: 15 5th Causality and relationship between variables: independence, independent and dependent variables, conditions of causality. Basics of contingency tables: understanding a contingency table. Row and column percentages, Cramer’s V. Readings: Social statistics (Lecture 7) 6th Summary and practice Theory: Properties of variables, central tendency and variability measures, contingency table Practice (SPSS): short analysis based on a research question using descriptive statistics and contingency tables 7th Descriptive statistics versus statistical inferences. Statistical estimation and statistical hypothesis test. T-tests. Recapitulation: sampling. Readings: Babbie (Statistical Analysis – Inferential statistics) 8th Continency table analysis as a statistical inference: chi-square test.  Controlling the relationship: three dimensional contingency tables. Readings: Babbie (Statistical Analysis – Inferential statistics) 9th Using latent variables: Indices, scales, principal component analysis, factors. Readings: Babbie (Statistical Analysis – Factor analysis) 10th Correlation and linear regression: linearity, Pearson’s correlation, equation of regression, regression coefficients, coefficient of determination. Homework: create an index, PCs or factors, interpret them. Use the created variable as a dependent variable of a regression. Interpret the results! Points: 25 Readings: Babbie (Statistical Analysis – regression), Social statistics (Lecture 9) 11th Regression in depth: assumptions and their violations – residual analysis, multivariate regression, interaction, statistical inference in regression, (GLM model), Q-Q plot 12th Consolidation, recapitulation. 13th Take home test: Answer a research question with the aim of learnt statistical tools and interpret the results (Points: 36)

Assessment method

Evaluation 40% of the students' assessments is based on homework assignments there will be two homeworks during the semester (please note the deadlines on the LMS) (15+25 points) Homework solutions are accepted individually or by groups of two students. In the latter case, both students upload the same file to the LMS  the filename must include the last names of both students the first line of the document should indicate if that this is a joint homework assignment of two students collected homework points will be credited to both authors the total points for homework will be 76 points. 36% of the evaluation is based on take home test on the last week Take home test will be accepted individually or in pair. n the latter case, both students upload the same file to the Canvas and the filename must include the last names of both students. 24% of the evaluation is based on the activity during the seminars (2 points per seminar, 24 points in total) Each part (Homework, seminar activity, take home test) should be above 50% for completing the course! Marks shall be based on the following percentages: 1 (fail): 0-49 % 2 (pass): 50-59 % 3 (satisfactory): 60-74 % 4 (good): 75-84 % 5 (excellent): 85-100 % In case of fail (performance below 50% in any part), the mark will be registered, and a colloquium will be held in the first two weeks of the exam period. According to the university regulation it is not possible to correct the final mark except the case of fail. Attendance at the class is mandatory. Evaluation cannot be given in case of 4 or more absences. In the latter case, an exam cannot be written in the exam period!

Bibliography

Literature and resources Németh, Renáta ; Simon, Dávid: Social Statistics. Budapest, Magyarország : Eötvös Loránd Tudományegyetem (2011) (available on LMS) Babbie, E. R. (2020). The practice of social research. Cengage learning. Online Statistics Education: An Interactive Multimedia Course of Study. Developed by Rice University (Lead Developer), University of Houston Clear Lake, and Tufts University. Internet: https://onlinestatbook.com/2/index.html (useful resource, more statistical, but with many visualizations and simulations) SPSS available for every student of ELTE, detailed instructions will be available on the LMS.

Programmes of the course