问题如下：
After applying data transformations, Steele scales the financial data using normalization. She notes that over the full sample dataset, the “Interest Expense” variable ranges from a minimum of 0.2 and a maximum of 12.2, with a mean of 1.1 and a standard deviation of 0.4.
Exhibit 1 Sample of Raw Structured Data Before Cleansing
Based on Exhibit 1, for the firm with ID #3, Steele should compute the scaled value for the “Interest Expense” variable as:
选项：
A. 0.008.
B. 0.083.
C. 0.250.
解释：
B is correct. Steele uses normalization to scale the financial data. Normalization is the process of rescaling numeric variables in the range of [0, 1]. To normalize variable X, the minimum value (Xmin) is subtracted from each observation
(Xi), and then this value is divided by the difference between the maximum and minimum values of X (Xmax – Xmin):
The firm with ID #3 has an interest expense of 1.2. So, its normalized value is calculated as:
Xi(normalized) =(1.2-0.2)/(12.2-0.2)=0.083
为什么不是（1.2-1.1）/0.4=0.25？
