[amp_mcq option1=”Data Scaling” option2=”Data Transformation” option3=”Data Normalization” option4=”Data Imputation” correct=”option4″]<\/p>\n
The correct answer is: Data Normalization<\/strong>.<\/p>\n Data normalization is the process of converting data values into a standard format to remove noise and variations. This is done by subtracting the mean value from each data point and then dividing it by the standard deviation. This ensures that all data points are on a similar scale and that any outliers are removed.<\/p>\n Data scaling is the process of rescaling data values to a common range. This is done by multiplying each data point by a constant value. This is often done to make data more comparable or to fit it into a specific range.<\/p>\n Data transformation is the process of changing the form of data values. This is done by applying a mathematical function to each data point. This is often done to make data easier to analyze or to improve its accuracy.<\/p>\n Data imputation is the process of filling in missing data values. This is done by estimating the missing values based on the available data. This is often done to improve the accuracy of data analysis.<\/p>\n","protected":false},"excerpt":{"rendered":" [amp_mcq option1=”Data Scaling” option2=”Data Transformation” option3=”Data Normalization” option4=”Data Imputation” correct=”option4″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[735],"tags":[],"class_list":["post-52936","post","type-post","status-publish","format-standard","hentry","category-data-collection-and-preprocessing","no-featured-image-padding"],"yoast_head":"\n