Test Your Knowledge
Question 1 of 4
Which of the following best describes the main difference between normalization and standardization?
Normalization uses the mean, while standardization uses the median
Normalization scales to a fixed range, while standardization centers around mean 0 with standard deviation 1
Normalization is only for categorical data, while standardization is for numerical data
Normalization removes outliers, while standardization preserves them
Question 2 of 4
In which scenario would normalization be more appropriate than standardization?
When performing Principal Component Analysis (PCA)
When dealing with features that have significantly different scales
When working with image processing tasks
When the algorithm assumes normally distributed data
Question 3 of 4
Why is standardization often preferred for anomaly detection tasks?
It preserves the original distribution of the data
It's more computationally efficient than normalization
It's less sensitive to outliers compared to normalization
It allows for easier interpretation of the original units
Question 4 of 4
In which of the following scenarios would you likely choose normalization over standardization?
When preparing data for a neural network with sigmoid activation functions
When conducting a t-test on your data
When performing k-means clustering
When applying linear regression to your dataset