ADVANCED QUANTITATIVE AND QUALITATIVE DATA ANALYSIS USING STATA
All associations that are being observed in any research must be valid, i.e. not due to bias. Multiple regression models are used to determine predictors. Therefore, research analysts, research scholars, Government practitioners, managers, market researchers, etc. should be able to understand and interpret multiple regression methods and outputs. This course is ideally suited to participants who have, or whose organizations may have, qualitative and/or quantitative data but are unsure of how to analyze them or are unsure of how to get the most information out of their data. Participants will be made aware of how they can confirm the hypotheses or answer research questions using various types of data and various types of analyses. Equally important, participants will be able to conduct inferential statistics and estimate measures of effect using STATA. They will be able to build causal or predictive statistical models and interpret outputs. In the same vein, they will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of their analysis in a way that is interpretable for clients or the public. The orientation of the course is towards theoretical, applied, computational well as field data-based research. This course covers topics in developing and testing theories using qualitative and quantitative methods. The course consists of four main parts (1) theoretical modeling: assumptions, deriving testable hypotheses or research questions (2) time series analysis (3) panel data analysis (4) Survey data analysis. Mainly, the course builds on inferential statistics. Participants will learn to STATA. STATA is arguably the best software for data management and statistical analysis. It is designed for researchers of all disciplines.
The primary objective of the course is to enable the participants to develop a suitable methodology for addressing the problem and learn about various tools and techniques to analyze and interpret the data quantitatively as well as qualitatively. Participants will learn how to identify problems to study, develop hypotheses, and research questions. Moreover, participants will learn how to specify independent and dependent variables and check for the validity and reliability of studies. Overall, the course will expose participants to the process of qualitative and quantitative statistical analysis of social science, education, business, and management problems in both the private and public sectors. In the process of learning, participants will be exposed to various techniques of large data handling and analysis through STATA.
At the end of the course, participants should be able to:
Knowledge and Understanding
- Demonstrate an understanding of statistical modeling
- Demonstrate understanding of multivariate analysis, factor analysis, correlation analysis, and reliability analysis.
- Understand and formulate study problems and statistical hypotheses.
- Develop an insight into the forecasting of time series
- Demonstrate competence in using excel and statistical software package, STATA
Intellectual/thinking / Cognitive Skills
- Analyze survey, time series, cross-section, and panel data
- Formulate inferences, calculating likelihoods, and make decisions
- Interpret statistical output/results
- Critically evaluate statistical models and forecasting tools
- Develop general skills in analyzing and exploring data, which can be used in different fields
Nature of regression analysis and review of basic statistical concepts
- Descriptive vs. Inferential statistics
- Random variables
- Mean, variance, covariance, and correlation
- Causation vs. Correlation.
The course is aimed at researchers who need to perform analysis on data from sample surveys as well as secondary data. Participants may be Faculty and Research Scholars (Masters & Ph.D. candidates), Statisticians, Research Analysts, Data Analysts, Economists, Program Managers, Market Researchers, Local and Central Government practitioners, Survey Agents, etc.
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