Research analytics

Description

This course introduces the fundamental concepts, principles, and methodologies of research analytics, focusing on data collection, processing, statistical analysis, interpretation, and evidence-based decision-making. students explore research design, systematic literature reviews, sampling techniques, variable measurement, and quantitative and qualitative research methods. the course develops practical skills in data management and analysis using python and microsoft excel, including data cleaning, descriptive statistics, data visualization, probability distributions, statistical inference, hypothesis testing, correlation analysis, a/b testing, regression analysis, and predictive modeling. students also examine text analytics, model validation, research data ethics, informed consent, privacy protection, and academic integrity. through case studies and project-based learning, students learn to select appropriate analytical methods, interpret research findings, prepare evidence-based analytical reports, and communicate results effectively in academic and professional contexts.

Course learning outcomes

1. 1

   CLO 1: Explain the fundamental concepts, principles, and stages of research analytics.

2. 2

   CLO 2: Apply appropriate data collection, sampling, and analytical methods to research problems

3. 3

   CLO 3: Analyze collected data using statistical and analytical techniques and identify relationships between variables.

4. 4

   CLO 4: Interpret analytical results, create appropriate visualizations, and prepare well-founded analytical reports.

5. 5

   CLO 5: Develop and present an analytical project individually or as part of a team to address a specific research problem.