BUSI4T215: Advanced Quantitative Data Analysis

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• To facilitate students in-depth engagement with a range of advanced approaches to quantitative data analysis.
• To develop students critical understanding of the logic of hypothesis testing and making causal claims.
• To provide students with hands-on experience in advanced analysis with state-of-the-science software tools.
• To facilitate students doctoral-level interpretation and writing skills for advanced quantitative data analysis.
• To develop students critical understanding of ethical implications when conducting quantitative research.

• Hypothesis testing and causal inference in the context of advanced quantitative techniques.
• Quantitative data management and data quality.
• Multiple regression for testing simple and complex moderation and mediation models
• Advanced approaches to data analysis (confirmatory factor analysis, structural equation modelling, multilevel modelling, time series)
• Software tools for advanced data analysis (e.g., MPlus, -Stata).

Subject-specific Knowledge:

• Critical understanding of statistical principles of data analysis
• Critical understanding of advanced quantitative data analysis approaches
• How to ensure data quality.

Subject-specific Skills:

• Ability to select relevant data analytical approaches
• Ability to interpret the results of advanced data analysis
• Ability to communicate quantitative research results, verbally and in writing.

Key Skills:

• Conducting advanced data analysis
• Using state-of-the-science software packages
• Interpreting advanced research results
• Writing and communicating advanced research results.

• The module will be delivered in a blended format, including lecture-type delivery, combined with tutor supported lab work (e.g., data analysis).
• The summative assessment (group component) and formative assessment are designed for students to learn from each other, strengthen the building of a doctoral community, and develop their teamwork skills for collaborative research.
• The summative assessment (individual) of the module is designed to facilitate students advanced quantitative data analysis and interpretation skills.
• Comprehensive reading and self-study materials will be provided online.

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