[LLN CLT] Update Translations #49
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Pull Request Overview
This PR improves Chinese translations in the Law of Large Numbers and Central Limit Theorem lecture. The changes focus on enhancing clarity and mathematical precision in the Chinese text.
- Corrects grammatical flow in the description of random vectors and matrices
- Expands the explanation of the continuous mapping theorem with more precise mathematical definition
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lectures/lln_clt.md
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| 其次，根据[连续映射定理](https://en.wikipedia.org/wiki/Continuous_mapping_theorem)，如果$\mathbf Z_n \stackrel{d}{\to} \mathbf Z$在$\mathbb R^k$中成立，且$\mathbf A$是常数且为$k \times k$矩阵，那么 | ||
| 其次，连续映射定理指出， 如果$g(\cdot)$是一个连续函数， 且随机变量序列$\{\mathbf{Z}_n\}$依分布收敛到随机变量$\mathbf{Z}$, 那么$\{g(\mathbf{Z}_n)\}$也依分布收敛到随机变量$g(\mathbf{Z})$。根据连续映射定理，如果$\mathbf Z_n \stackrel{d}{\to} \mathbf Z$在$\mathbb R^k$中成立，且$\mathbf A$是常数且为$k \times k$矩阵，那么 |
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There are inconsistent spacing issues around punctuation in the Chinese text. There should be no space before commas (， should be ，) and the spacing around mathematical notation should be consistent.
| 其次，连续映射定理指出， 如果$g(\cdot)$是一个连续函数， 且随机变量序列$\{\mathbf{Z}_n\}$依分布收敛到随机变量$\mathbf{Z}$, 那么$\{g(\mathbf{Z}_n)\}$也依分布收敛到随机变量$g(\mathbf{Z})$。根据连续映射定理，如果$\mathbf Z_n \stackrel{d}{\to} \mathbf Z$在$\mathbb R^k$中成立，且$\mathbf A$是常数且为$k \times k$矩阵，那么 | |
| 其次，连续映射定理指出，如果$g(\cdot)$是一个连续函数，且随机变量序列$\{\mathbf{Z}_n\}$依分布收敛到随机变量$\mathbf{Z}$, 那么$\{g(\mathbf{Z}_n)\}$也依分布收敛到随机变量$g(\mathbf{Z})$。根据连续映射定理，如果$\mathbf Z_n \stackrel{d}{\to} \mathbf Z$在$\mathbb R^k$中成立，且$\mathbf A$是常数且为$k \times k$矩阵，那么 |
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@nisha617 if you agree with this -- you can select Commit suggestion, but feel free to ignore it if it isn't of value -- just click Resolve conversation. Thanks.
This PR updates the translation in lln_clt.