Outcomes
After attending this module the attendees should be able to
- Make participants well aware of the practical problems which are to be confronted during higher degree dissertation
- Have a clear understanding of planning the research proposal and developing a research report/dissertation
- Develop scientific attitude and broad understanding of the use of research
- Develop succinct hypothesis based on relevant research gap, support it empirically, theoretically and econometrically and tie results to outcomes viable for practitioners
- Understand qualitative and quantitative research methods and their application to research
- Develop and validate primary research instrument for data collection and to manage field operations.
- Develop an understanding regarding importance of theory development
- Participants will develop a basic understanding of the relationship between specific research designs and statistical approaches
- Operate SPSS software, step by step, starting from the initial level till the advanced inferential statistical analysis and interpretation
- Reference data using online and offline software’s
- Attendees will appreciate the basic elements of the publishing process
Workshop content
Topic Selection & problem Identification
- The challenges of managing self & research environment
- Basic factors to select research topic
- Focusing on research problem
- Delimitating research
Literature Reviewing Techniques
- Literature reviewing techniques
- Drafting structure of Literature Review
- Identifying controversies & GAP
- Writing Literature review (Citation styles, paraphrasing, Language focus, Reporting verbs)
- Theoretical and conceptual framework development
Methodological Framework
- Sampling technique selection, Sample size calculation, Sample to generalizability
- Variable type & Data collection technique
- Scale development techniques
SPSS
- Introduction stage
- SPSS basics; Output and data view, Data coding, Defining Variable & data entry, right scale allocation
- Data preparation stage
- Computing Variables, Dealing with missing variables, Creating dummy variables, variable re-specification, scale transformation, Dealing with unreliable data (reliability and validity analysis); factor analysis
- Data Analysis stage: Equip attendees with the understanding of the relationship between specific research designs, statistical approaches, analysis, interpretation and managerial implications
- Uni-variate statistics: frequencies including measures of location, measures of variability, and measures of shape, cross-tabulations, chi-square. One Sample t-test, Independent sample t-test, Analysis of variance (ANOVA), Analysis of Covariance (ANCOVA)
- Multi-variate statistics:
- MANOVA and MANCOVA analysis
- Product moment correlation, partial correlation, and show how they provide a foundation for regression analysis
- Bivariate regression analysis and describe the general model, estimation of parameters, standardized regression coefficient, significance testing, Specialized techniques used in multiple regression analysis, particularly stepwise regression, regression with dummy variables, and Assumptions of Regression analysis
Selling your research & Impact factor publication
- Citation & referencing in research using Endnote (X4)
- Ways of writing abstract
- Tips to get impact factor publication
- Techniques of getting fund for conference/ research paper publication
- Selling your research work
Workshop duration: 2-3 days maximum
Note: Send email at register@gcbms.org and/or register.gcbms@gmail.com to register for research workshop, before/after conference.
We also arrange customized “research workshop” for universities/institutes, on special request, for further details, send email at register@gcbms.org and/or register.gcbms@gmail.com.