A conditional probability

Therefore, The probability of an event( B) P( A) is given by : Example: A food poisoning infection, 99 were In the cases of the disease among the 158 people attending( a ) Entertainment. The probability queue management system of a person It is random : Once that occurs in a number of ( ) The number of times it can happen B. = 99 () 0.6266 158 B.

Conditional probability == For example, toxic Feed entary, the probability that There is a certain person To 0.6266. However, Disease( with a probability ) If you need to change Do you know the food eaten( B ) Person. This introduces the idea of Conditional probability or PR is given obability B has occurred.

Probability B conditional on a given ad Defined The number of A and B occur together (/ ) How many times B occurs PAB = Example : 133 people at the party, Turkey( B) Eat Of these, 95 false( a) Sout Determine the probability of the disease in people who ate turkey dinner. Expressed as a conditional probability.

Terms of queue management system subjective

That is : Sickened number of people eating in Turkey (/ ) The number of people ate turkey PA B queue management system 95( 0.71 133 PA B Critical Events == Expressed Events Specific combinations (A and B occur) and Alternative expressed (A or B occurs ), the That complex phenomena. P (A and B): Probability That A and B occur together.

If A and B JU can occur NTS are mutually Exclusive, then P (A and B)= 0 P (A or B): queue management system the probability that A occurs or B occurs or both of them Occur. In other words, P (A or B) expresses the probability that at least one A or B events ocurraRegla times The probability of two events A and B with a And B is defined to occur As : P (A and queue management system B)= P( A/ B) P( B ) When A and B are independent events, we P (A and B)= P( A) P (B) Example : A significant side effects The pursuit of a drug 10% of patients taking it. Two patients with a doctor queue management system who the drug has been taken.

Ramya ‘s L is the probability that the two Experience side effects ? A patient does not affect the occurrence of side effects Other( independent) as the consequences. P( two colatera effects occurred, In addition to Les)= 0.1 x 0.1= 0.01 (1%) Rule : Given two events A and B, A or B is defined as any possibility of P (A or B)= P( A) P( B) P (A and B).

When A and B are mutually exclusive P (A or B)= P( A)+ P (B) Example : What is the probability that the Patients with at least one Medical side effects ? A or B, or a patient Both effects may be Side( events In a study of hypertensive organ damage (Entwisle and High blood pressure al, 1977 ) Cases treated in a hospital University. Table data compiled from 306 cases Damage from the newly identified high blood pressure, and displays data Terminal element of the severity of hypertension. Answer the following questions 1.

Refer to those responsible

Male, female defining the probability. Queue management system there are three basic ways to define probability. Definitions of these three approaches are presented Different opinion : 9 Classical definition. 9 The relative frequency of queue management system occurrence. 9 Subjective probability.

Classical Probability We varaiyarukkirom probability : An event occurring Number of results occur Probability = The number of possible outcomes Each of the possible consequences should be equal Possible. Example : Likely to be born a girl= 1/2Probabilidad Classic ¾ Classical probability, It is often referred to as Because the probability of pre- we will also use Change coins, dice any such predictable Load and decks of cards normal.

We can System Response Without advance a coin, flipping a tie or draw a card. Not We are queue management system doing tests Donations Reach Results. ¾ This approach has serious probability When problems trying Problems applying The results will be less predictable. ¾ Refers to a kind of classical probability Relative symmetry in the event mundoFrecuencia In the nineteenth century, the British statistics, Theoretical foundations Interests Principles of calculating risks Life insurance and trading began, Collect data on birth and death.

Cases an event queue management system

Currently, this approach is called The relative frequency Event An event. The relative frequency of occurrence Probability is defined as ¾ Observed relative frequency of an event when Large number of attempts, or ¾ The event is part of a long- time When conditions are stable. The relative queue management system frequency of use with a probability of passing.

Determine Something happened in the past, how often use this number to calculate the probability of the event Relative new phenomenon futuro. Frecuencia Example : A vulnerability( probability of occurrence ) : The disease is estimated The number of cases Distribution = Population at risk When we use the relative frequency approach Installation possibilities, we get To increase the probability of Subjective observaciones. Probabilidades In probability people ‘s beliefs Probability estimate. Subjective probability can be defined as Assigned a probability of an event We provide evidence-based, personal Available.

Presented evidence that The relative frequency of occurrence of the form Past events, or may simply A trust is considered. Subjective probabilities ¾ Subjective evaluations We Probability More flexible than OT Ros two approaches. Decision makers can They use a mix of hand any evidence Personal feelings about the situation.

Subjective probability provided services Only when events occur more frequently At one time or two times a very small number. ¾ Almost all social decisions, such as queue management system senior Management The specific and unique circumstances, which refer to those responsible for The results are used as collateral Probability nsiderable Probability subjetivaCálculo Chance best defined in terms of relative frequency.

A test result for probability

The concept of probability is often In the area of ​​health communication. Examples ¾ Patient X is a chance for a doctor says 50% of live surgery Flag, or is a patient and Tene 80% chance Or a specific disease ; ¾ With a power Minist Health erio; Announces Press this summer that is likely to be1 % Unleash an epidemic of cholera in the capital. Why is it important to learn queue management system Calculate probabilities ?

Medicine is a science INEXA CTA so the doctor can rarely predict with absolute certainty the outcome. Create diagnosis The doctor should have all possible information about the patient For example should be : ¾ History Editor ¾ Perform a physical examination ¾ Order laboratory studies ¾ X- rays, etc., results. Want to learn why Calculate probabilities ? Although no effect Test, is the most accurate Affect the probability of The presence or absence of a Disease.

The basis of the queue management system

I calculate uncertainty Decision-making process nherente, the doctor relies on the Probability theory Therefore : Must understand the odds The process of mental Decision-making in the health sector. Why queue management system is it important to learn Calculate probabilities ? Probability theory allows the doctor The results of the Population Of Patients on information Model It ‘s extracted from the population. This process is called Statistical inference. History queue management system of Probability. Berooulli Jacob (1654- 1705), Abraham de Moivre (1667- 1754), Rev.

Thomas Bayes (1702- 1761) and Joseph Lagrange (1736- 1813) created Formulas and techniques for calculating Probability. In the nineteenth century, Pierre Simon, evidence Laplace (1749- 1827), the initial ideas for a unified and Compiled the first comprehensive theory of probability. Used queue management system probability theory Tables and successfully, More importantly. Career Requires a precise knowledge of the risks insured loss. Analysis of several learning centers The probability of an instrument Understanding of social phenomena.

Our review of the need for dealing with uncertainty and leads to Probability theory. Organize information and review Formal, communication, able to recognize our assumptions Others cause us to base decisions taken sólidas. Concept probability. Probability Probability Something is happening. The possibilities are expressed Fractions or That between decimals One And Zero. ? A probability of zero Does not mean anything Going Happen.

Indicates that the chance of something happening Based on siempre.Conceptos Probability A Randomized Trial Everyone knows, it becomes a Potential effects, but do not know if it will happen Example : A child is born Random testing, The child seems to be happening Ron or female, but it does not seem what is the effect.

A Event One or more of the possible outcomes is Random testing. Example : Random test cases: male, based on mujerConceptos Probability A set of all possible outcomes That test Sample interval Testing. Example: Sample interval It is said that the two events Strained If a And they can happen in a moment. When is the list of events can be Adds all the results of possible, that it is in the list Collectively exhaustive.