Survey Analytics
About This Course
Surveys made widespread by the Internet are a common tool for organizations to understand broader populations without needing individual assessments. This course covers essential tools for conducting survey projects, beginning with questionnaire design and relevant statistical background. We'll explore three common sampling designs fundamental for large-scale surveys, delve into factor analysis for estimating unobservable traits like attitudes, and examine natural language processing techniques for analysing open-ended questions, offering deeper insights than simple frequency counts or word clouds. Utilizing the statistical computing language R, which offers extensive packages for survey analytics, participants will gain a comprehensive understanding of modern survey methodologies.
What You'll Learn
2. Assess the quality of the survey design and identify elements that contribute to its effectiveness.
3. Critique how a well-structured sampling design can enhance the efficiency of gathering information from a large population.
4. Apply and interpret factor analysis to uncover underlying factors, enabling the reduction of complex survey data into clear, meaningful dimensions.
5. Evaluate sentiment analysis results and topic modeling for deriving insights from open-ended responses.
Entry Requirements
Achieve a minimum NUS GPA of 2.50 for the Executive Certificate in Intermediate Data Analytics for the Maritime Industry