[amp_mcq option1=”it relates inputs to outputs.” option2=”it is used for prediction.” option3=”it may be used for interpretation.” option4=”it discovers causal relationships.” correct=”option4″]<\/p>\n
The correct answer is D. Regression does not discover causal relationships.<\/p>\n
Regression is a statistical method that is used to find the relationship between two or more variables. It can be used to predict the value of one variable based on the values of the other variables. Regression can also be used to understand the relationship between variables, such as how one variable affects another. However, regression cannot be used to determine cause and effect.<\/p>\n
For example, if you regress height on weight, you will find that there is a strong positive relationship between the two variables. This means that taller people tend to weigh more, on average. However, this does not mean that height causes weight. It is more likely that both height and weight are caused by a third variable, such as genetics.<\/p>\n
In conclusion, regression is a powerful tool that can be used to understand the relationship between variables. However, it is important to remember that regression cannot be used to determine cause and effect.<\/p>\n","protected":false},"excerpt":{"rendered":"
[amp_mcq option1=”it relates inputs to outputs.” option2=”it is used for prediction.” option3=”it may be used for interpretation.” option4=”it discovers causal relationships.” 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":[729],"tags":[],"class_list":["post-55381","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"\n