{"id":1495,"date":"2023-10-30T11:50:10","date_gmt":"2023-10-30T11:50:10","guid":{"rendered":"https:\/\/myknowledgehub.org\/?p=1495"},"modified":"2023-11-26T11:29:59","modified_gmt":"2023-11-26T11:29:59","slug":"research-methodology-chapter-6-5","status":"publish","type":"post","link":"https:\/\/myknowledgehub.org\/index.php\/2023\/10\/30\/research-methodology-chapter-6-5\/","title":{"rendered":"Research Methodology Chapter 8.1"},"content":{"rendered":"\t\t
\n\t\t\t\t
\n\t\t\t\t\t
\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"bayesian,\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Probability Distribution<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Definition and Types <\/h2><\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

In the field of statistics, probability distribution refers to the mathematical function that describes the likelihood of different outcomes occurring in a particular event or experiment. <\/span>A probability distribution is a function that describes the likelihood of different outcomes in a random event<\/b>. It provides a way to assign probabilities to each possible outcome of a random event, based on the likelihood of that outcome occurring<\/span><\/span>. <\/span><\/span><\/p>\n

 <\/span><\/p>\n

There are several types of probability distributions, each with its own characteristics and applications. <\/span><\/p>\n

 <\/span><\/i><\/b><\/span><\/p>\n

Discrete probability distributions<\/span><\/i><\/b><\/span>: These are used when the possible outcomes of a random event are discrete, or separate and distinct, rather than continuous. Examples include the roll of a die, the flip of a coin, and the outcome of a lottery draw. Common discrete probability distributions include the Binomial distribution<\/b>, the Geometric distribution<\/b>, and the Poisson distribution<\/b>.<\/span><\/span><\/p>\n

 <\/span><\/i><\/b><\/span><\/p>\n

Continuous probability distributions<\/span><\/i><\/b><\/span>: These are used when the possible outcomes of a random event are continuous, or can take on any value within a certain range. Examples include the height of a person, the weight of an object, and the time it takes for an event to occur. Common continuous probability distributions include the Normal distribution<\/b>, the Uniform distribution<\/b>, and the Exponential distribution<\/b>.<\/span><\/span><\/p>\n

 <\/span><\/span><\/p>\n

Multivariate probability distributions<\/span><\/i><\/b><\/span>: These are used when there are multiple random variables involved in a single event. Examples include the distribution of height and weight for a group of people, or the distribution of temperatures in different locations. Common multivariate probability distributions include the Multivariate Normal distribution <\/b>and the Multivariate Uniform distribution<\/b>.<\/span><\/span><\/p>


<\/span><\/span><\/p>


<\/span><\/span><\/p>

In the next three chapters we will learn in detail about 1) Normal distribution, 2) Binomial distribution, and 3) Poisson Distribution. <\/span><\/span><\/p>\n


<\/span><\/span><\/p>\n


<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

\n\t\t\t\t\t
\n\t\t
\n\t\t\t\t\t
\n\t\t
\n\t\t\t\t\t
\n\t\t
\n\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\tBack to the Content<\/span>\n\t\t\t\t\t<\/span>\n\t\t\t\t\t<\/a>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Probability Distribution Definition and Types In the field of statistics, probability distribution refers to the mathematical function that describes the likelihood of different outcomes occurring in a particular event or experiment. A probability distribution is a function that describes the likelihood of different outcomes in a random event. It provides a way to assign probabilities to each possible outcome of …<\/p>\n

Research Methodology Chapter 8.1<\/span> Read More »<\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","footnotes":""},"categories":[1],"tags":[],"class_list":["post-1495","post","type-post","status-publish","format-standard","hentry","category-blog"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/posts\/1495","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/comments?post=1495"}],"version-history":[{"count":20,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/posts\/1495\/revisions"}],"predecessor-version":[{"id":1817,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/posts\/1495\/revisions\/1817"}],"wp:attachment":[{"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/media?parent=1495"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/categories?post=1495"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/myknowledgehub.org\/index.php\/wp-json\/wp\/v2\/tags?post=1495"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}