{"id":47607,"date":"2024-04-15T22:29:13","date_gmt":"2024-04-15T22:29:13","guid":{"rendered":"https:\/\/exam.pscnotes.com\/mcq\/?p=47607"},"modified":"2024-04-15T22:29:13","modified_gmt":"2024-04-15T22:29:13","slug":"this-technique-associates-a-conditional-probability-value-with-each-data-instance","status":"publish","type":"post","link":"https:\/\/exam.pscnotes.com\/mcq\/this-technique-associates-a-conditional-probability-value-with-each-data-instance\/","title":{"rendered":"This technique associates a conditional probability value with each data instance."},"content":{"rendered":"<p>[amp_mcq option1=&#8221;linear regression&#8221; option2=&#8221;logistic regression&#8221; option3=&#8221;simple regression&#8221; option4=&#8221;multiple linear regression&#8221; correct=&#8221;option2&#8243;]<!--more--><\/p>\n<p>The correct answer is B. Logistic regression.<\/p>\n<p>Logistic regression is a statistical method that is used to predict the probability of an event occurring. It is a type of regression analysis that is used to model a binary dependent variable. The dependent variable can be either 0 or 1, such as whether or not a customer will purchase a product.<\/p>\n<p>Logistic regression is a powerful tool that can be used to make predictions about a variety of events. It is often used in marketing, finance, and healthcare.<\/p>\n<p>A. Linear regression is a statistical method that is used to model the relationship between a dependent variable and one or more independent variables. The dependent variable can be continuous, such as height or weight. The independent variables can be continuous or categorical.<\/p>\n<p>C. Simple regression is a type of linear regression that is used to model the relationship between one dependent variable and one independent variable.<\/p>\n<p>D. Multiple linear regression is a type of linear regression that is used to model the relationship between one dependent variable and two or more independent variables.<\/p>\n<p>In conclusion, the correct answer is B. Logistic regression.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>[amp_mcq option1=&#8221;linear regression&#8221; option2=&#8221;logistic regression&#8221; option3=&#8221;simple regression&#8221; option4=&#8221;multiple linear regression&#8221; correct=&#8221;option2&#8243;]<\/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-47607","post","type-post","status-publish","format-standard","hentry","category-machine-learning","no-featured-image-padding"],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v22.2 (Yoast SEO v23.3) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>This technique associates a conditional probability value with each data instance.<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/exam.pscnotes.com\/mcq\/this-technique-associates-a-conditional-probability-value-with-each-data-instance\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"This technique associates a conditional probability value with each data instance.\" \/>\n<meta property=\"og:description\" content=\"[amp_mcq option1=&#8221;linear regression&#8221; 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