在有些半導體的問題上，礙於數據取得困難，或是資料共有、一致性的問題，都存在著待分析資料不足的問題，如何在數據量以及變數量的多寡上面的取捨，也是在使用統計分析時需要注意的一項重點。
面對龐大的資料，我們也作了篩選的動作，利用初步的統計方法，檢視出資料裡對我們應變數關係較明顯的幾個重要變數，藉由一個門檻值來篩選，如此一來，再作進一步分析時，所有變數一起做分析造成的數據量問題，便能夠得到改善。
我們為了解決數據量和機台數量的問題，使用了分群的方法，有效的將機台數量降低，使我們在利用統計方法建立模型時，不再為了變數量太多造成模型過度配適(over-fit)的問題所困擾。

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