Overview
For secondary school students, our curriculum will delve deeper into technical aspects of research. Building upon their foundational knowledge, we will introduce advanced data analysis techniques such as regression, numerical solving, and more (on top of the content covered in primary school general curriculum page). We will discuss with each respective school and their teachers to tailor and finalize the curriculum. Moreover, we will also provide exposure to cutting-edge concepts in research such as machine learning and artificial intelligence, which are increasingly integral to modern-world research regardless of disciplines. Similarly, we will also organize mini-projects (geared at a higher level) for students to experience the entire research process.
Advanced Data Analysis Techniques
- Hypothesis Testing
- Null hypothesis, alternative hypothesis.
- Mean, median, and standard deviation.
- Statistical Methods
- Significance level: a way to numerically quantify how different two data sets are.
- Introduction to various tests: e.g., Mann-Whitney U test, T test, etc.
- Regression (Simple lesson on Excel)
- Linear regression, what is the R-squared value, and some mathematical backgrounds.
- Non-linear regression.
- Error Analysis
- Error propagation techniques, error bar.