| Date | # | Title / Contents | Handout |
| 2025/4/10 | 1 | TA Session 1 | |
| Matrix Algebra 1 | |||
| 2025/4/17 | 2 | Session 2 | |
| Matrix Algebra 2 | |||
| 2025/4/24 | 3 | Session 3 | |
| Matrix Algebra 3 | |||
| 2025/5/8 | 4 | TA Session 4 | |
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1. Sets 2. Probability 3. Bayes' Theorem 4. Random Variable |
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| 2025/5/15 | 5 | TA Session 5 | |
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1. Discrete Random Variable 2. Multiple discrete random variables 3. The rule for calculating the expected value 4. The rule for calculating the variance 5. Typical discrete random variables Appendix |
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| 2025/5/22 | 6 | TA Session 6 | PDF |
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1. Continuous Random Variable 2. Cumulative Distribution Function (CDF) 3. Probability Density Function (PDF) 4. Uniform Distribution 5. Expectation and Variance of Continuous Random Variables 6. Joint Distribution and Marginal Distribution 7. Covariance and Correlation Coefficient 8. Independence 9. Conditional Probability and Conditional Expectation |
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| 2025/5/29 | 7 | TA Session 7 | |
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1. Normal Distribution 2. Standard Normal Distribution 3. Chi-Squared Distribution 4. t-Distribution 5. Degrees of Freedom |
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| 2025/6/5 | 8 | TA Session 8 | PDF exercise |
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1. Relationship Between Population and Sample 2. Law of Large Number 3. CLT 4. Sampling Distribution of Sample Variance 5. Sample Variance under Normal Distribution 6. Standardisation of the sample mean using the sample variance |
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| 2025/6/12 | 9 | TA Session 9 | |
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1. Point Estimation 2. Interval Estimation |
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| 2025/6/19 | 10 | TA Session 10 | |
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1. The Idea of Hypothesis Testing 2. Test Statistics 3. One-Sided vs Two-Sided Tests 4. Testing the Difference of Means 5. Type I and Type II Errors |