A Priori Probability  Explained
What is A Priori Probability?
 Marketing, Advertising, Sales & PR
 Accounting, Taxation, and Reporting
 Professionalism & Career Development

Law, Transactions, & Risk Management
Government, Legal System, Administrative Law, & Constitutional Law Legal Disputes  Civil & Criminal Law Agency Law HR, Employment, Labor, & Discrimination Business Entities, Corporate Governance & Ownership Business Transactions, Antitrust, & Securities Law Real Estate, Personal, & Intellectual Property Commercial Law: Contract, Payments, Security Interests, & Bankruptcy Consumer Protection Insurance & Risk Management Immigration Law Environmental Protection Law Inheritance, Estates, and Trusts
 Business Management & Operations
 Economics, Finance, & Analytics
 Courses
Table of Contents
What is A Priori Probability?How does A Priori Probability Work?Examples of A Priori ProbabilityPriori Probability Types Priori Probability Uses Advantages of Prior Probability Limitation of Using Priori Probability in CalculationKey TakeawaysAcademic Research on A Priori ProbabilityWhat is A Priori Probability?
A priori Probability refers to the logical estimation of an incidents probability. It can also be explained as a situation where one estimates a circumstance or current information about the position of something. This probability deals with independent event whereby the possibility of a given event happening is not in any way influenced by past events.
Back to: RESEARCH, ANALYSIS, & DECISION SCIENCE
How does A Priori Probability Work?
Priori probability calculation is often done through deductive reasoning. This is so because, in order to determine the number of the possible outcome of any occurence, one must apply logic. Also, this type of probability is based on prior information when making a conclusion.
Examples of A Priori Probability
When tossing a coin, the possibility of it landing on a head or a tail in the second or subsequent toss is not in any way dependent on the first or previous result. Therefore, the chances of landing either side are equal hence the probability will definitely be 50%. The probability can also apply to a firms earnings where whether the firm will make a profit, a loss or break even at any given year, the probability of each of the events happening is equal. In this case, the probability will, therefore, be of each event occurring. It is important to note that in Priori probability, experts draw a conclusion about the outcome of an event before looking at any statistics. Meaning the Priori probability is used to estimate the occurrence of an event before the event actually happens.
Priori Probability Types
There are two types of Priori probability. The difference between the two probability is explained using Bayesian inference. They are as follows:
 PrioriThis refers to capturing of general knowledge about a given statistics before looking at it. This means conclusions about the data is made before it is analyzed.
 Posteriori This represents knowledge that includes the results. This means, in this type of probability, the outcome of an event is included in the conclusive results. Meaning the data about an event is analyzed before a conclusion is drawn.
Priori Probability Uses
 The Priori probability estimates are applied on a nonlinear equation root during an evaluation.
Advantages of Prior Probability
 The main advantage of using this method of calculation is that the procedure has no assumptions.
Limitation of Using Priori Probability in Calculation
 The major limitation about prior probability is that it only applies to a specific set of events (it is finite). For this reason, it can only be calculated for those events that are naturally independent. This is because the probability of most events happening is through conditioning to a certain percentage. The experiment is, therefore, not applicable where the outcomes are likely not to be equal.
 The experiment may fail especially when the figure of the possible experiment results is infinite (immeasurable).
 Difficult to estimate probabilities to the desired accuracy. You will need large sample sizes in order to get accurate results.
Key Takeaways
 The conclusion is made prior knowledge or before analyzing any data.
 It involves deductive reasoning (logic deduction).
 It has a basic assumption that the results of a random experiment are likely to be equal.