[amp_mcq option1=”To make predictions” option2=”To find patterns” option3=”To summarize data” option4=”To transform data” correct=”option1″]<\/p>\n
The primary objective of exploratory data analysis (EDA) in Data Science is to find patterns in data. EDA is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making.<\/p>\n
A. To make predictions is not the primary objective of EDA. While EDA can be used to identify patterns that can be used to make predictions, this is not its primary goal. The primary goal of EDA is to find patterns in data.<\/p>\n
B. To find patterns is the primary objective of EDA. EDA is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. One of the most important aspects of EDA is finding patterns in data.<\/p>\n
C. To summarize data is not the primary objective of EDA. While EDA can be used to summarize data, this is not its primary goal. The primary goal of EDA is to find patterns in data.<\/p>\n
D. To transform data is not the primary objective of EDA. While EDA can be used to transform data, this is not its primary goal. The primary goal of EDA is to find patterns in data.<\/p>\n","protected":false},"excerpt":{"rendered":"
[amp_mcq option1=”To make predictions” option2=”To find patterns” option3=”To summarize data” option4=”To transform data” correct=”option1″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[734],"tags":[],"class_list":["post-43897","post","type-post","status-publish","format-standard","hentry","category-introduction-to-data-science","no-featured-image-padding"],"yoast_head":"\n