Study-Unit Description

Study-Unit Description


CODE SOC5018

 
TITLE Research Analysis in Practice

 
LEVEL 05 - Postgraduate Modular Diploma or Degree Course

 
ECTS CREDITS 5

 
DEPARTMENT Sociology

 
DESCRIPTION The study-unit will be divided into two key topic areas: quantitative data analysis, and qualitative data analysis. Each will have an introductory theoretical component where the key concepts will be introduced in a lecture format, followed by blended theoretical/ hands-on practical application sessions using dedicated research data analysis IT software.

The qualitative theoretical component will cover key topics such as: Thematic Framework Analysis , Narrative Analysis, Interpretive Phenomenological Analysis.

The theoretical component will focus on different ways of collecting and presenting data, with emphasis on optimal use of graph displays and will introduce the theory related to normality of data and parametric/non-parametric tests.

Study-unit Aims:

QUANTITATIVE

To introduce the key concepts and techniques in quantitative data analysis which will include:
• different ways of collecting and presenting data, with emphasis on optimal use of graph displays;
• normality of data and parametric/non-parametric tests;
• optimal use of different statistical tests and how they work.

To offer a theoretical and hands-on grounding in statistical analysis and the use of SPSS which will include:
• appropriate use of tests of normality; parametric, independent and non-parametric tests;
• efficient and effective use of graphical displays of data and findings.

QUALITATIVE

To introduce some of the key concepts and techniques in qualitative data analysis which will include Thematic framework analysis, Narrative analysis, Interpretive Phenomenological Analysis.

To offer a hands-on introduction to nVIVO qualitative analysis software which will include:
• creating nVIVO workspace;
• importing data in to nVIVO;
• coding and making nodes;
• working with demographic data;
• summarizing data in framework matrices;
• vizualisation: charts, models, graphs, treemaps, cluster analysis diagrams.

Learning Outcomes:

1. Knowledge & Understanding
By the end of the study-unit the student will be able to:

• demonstrate clear understanding of sampling techniques and data collection methods, sample size calculation when analysing quantitative data;
• demonstrate variable generation and data entry in SPSS;
• analyse data using graphical and tabular displays in SPSS;
• analyse variables with multiple responses in SPSS;
• apply appropriate tests of normality; parametric, independent and non-parametric tests in SPSS;
• apply appropriate qualitative analysis techniques to qualitative data in a way that leads to reliable and convincing findings;
• use nVIVO software on qualitative data to analyse using codes and nodes, and to summarise in framework matrices;
• use nVIVO software to produce appropriate and effective visual displays of data.

2. Skills
By the end of the study-unit the student will be able to:

• form a critical opinion on quantitative empirical data analysis in academic publications based on sound understanding of efficacy of statistical methods used;
• form a critical opinion on qualitative empirical data analysis in academic publications based on a sound understanding of validity and reliability indicators in presentation of data;
• apply qualitative data analysis techniques to raw data in a way that offers findings that are reliable and valid;
• apply quantitative data analysis techniques to raw data that produce statistically sound findings;
• use SPSS software to analyse, and graphically display quantitative data and results coherently and efficiently;
• use nVIVO software to analyse qualitatative data and results coherently and efficiently.

Main Text/s and any supplementary readings:

MAIN TEXTS

- FIELD, A., 2013. Discovering statistics using IBM SPSS statistics. London Thousand oaks New Delhi: SAGE.
- SILVERMAN, D., 2015. Interpreting qualitative data: A guide to the principles of qualitative research. London, Thousand Oaks, New Delhi: SAGE.

SUPPLEMENTARY TEXTS

- ALVESSON, M., 2011. Interpreting interviews. SAGE.
- DE VAUS, D., 2013. Surveys in social research. London and New York : Routledge.
- WHEELAN, C., 2014. Naked statistics: stripping the dread from the data. WW Norton & Company.

 
STUDY-UNIT TYPE Lecture, Independent Study and Practical

 
METHOD OF ASSESSMENT
Assessment Component/s Resit Availability Weighting
Assignment Yes 40%
Project Yes 60%

 
LECTURER/S Michael Briguglio
Liberato Camilleri
Gillian M. Martin (Co-ord.)
Emanuel Said
Valerie Visanich
Christina Zarb

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the description above applies to study-units available during the academic year 2021/2. It may be subject to change in subsequent years.

https://www.um.edu.mt/course/studyunit