DCA

DCA

This course offers a detailed exploration of the methodologies and techniques essential for effective data collection and analysis. Students will delve into both theoretical concepts and practical applications, gaining proficiency in gathering and interpreting data to support decision-making in various fields.

Key areas of focus include:

• Data Collection Methods: Understanding and implementing diverse data collection techniques such as surveys, interviews, experiments, and observational studies.
• Survey Design and Sampling: Crafting effective surveys and questionnaires, selecting appropriate sampling methods, and ensuring representative samples.
• Data Cleaning and Preparation: Learning the best practices for preparing data for analysis, including handling missing data, data transformation, and ensuring data quality.
• Statistical Analysis: Applying statistical methods to analyze data, including descriptive statistics, inferential statistics, and hypothesis testing.
• Data Visualization: Utilizing tools and techniques to present data clearly and effectively, making complex data accessible and understandable through visual representation.
• Software Proficiency: Gaining hands-on experience with industry-standard software such as Excel, SPSS, R, or Python for data analysis and visualization.

Through a combination of lectures, hands-on labs, and real-world projects, students will develop the skills necessary to conduct rigorous data collection and analysis. By the end of the course, students will be prepared to apply these skills in academic research, business analytics, policy-making, and other professional contexts, driving informed decisions and strategic planning.