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<document xmlns="http://cnx.rice.edu/cnxml" xmlns:md="http://cnx.rice.edu/mdml/0.4" xmlns:bib="http://bibtexml.sf.net/" xmlns:m="http://www.w3.org/1998/Math/MathML" id="new">
  <name>Probability Topics: Terminology</name>
  <metadata>
  <md:version>1.4</md:version>
  <md:created>2008/05/08 15:11:46 GMT-5</md:created>
  <md:revised>2008/07/31 10:11:08.317 GMT-5</md:revised>
  <md:authorlist>
      <md:author id="billowsky">
      <md:firstname>Barbara</md:firstname>
      
      <md:surname>Illowsky</md:surname>
      <md:email>illowskybarbara@deanza.edu</md:email>
    </md:author>
      <md:author id="sdean">
      <md:firstname>Susan</md:firstname>
      
      <md:surname>Dean</md:surname>
      <md:email>deansusan@deanza.edu</md:email>
    </md:author>
  </md:authorlist>

  <md:maintainerlist>
    <md:maintainer id="cnxorg">
      <md:firstname/>
      
      <md:surname>Connexions</md:surname>
      <md:email>cnx@cnx.org</md:email>
    </md:maintainer>
  </md:maintainerlist>
  
  <md:keywordlist>
    <md:keyword>A AND B</md:keyword>
    <md:keyword>A OR B</md:keyword>
    <md:keyword>chance</md:keyword>
    <md:keyword>conditional</md:keyword>
    <md:keyword>equally likely</md:keyword>
    <md:keyword>event</md:keyword>
    <md:keyword>experiment</md:keyword>
    <md:keyword>frequency</md:keyword>
    <md:keyword>key terms</md:keyword>
    <md:keyword>long term</md:keyword>
    <md:keyword>outcome</md:keyword>
    <md:keyword>Probability</md:keyword>
    <md:keyword>relative</md:keyword>
    <md:keyword>sample space</md:keyword>
    <md:keyword>Statistics</md:keyword>
    <md:keyword>Terminology</md:keyword>
  </md:keywordlist>

  <md:abstract>This module defines several key terms related to Probability.</md:abstract>
</metadata>
  <content>
    <para id="delete_me">Probability measures the uncertainty that is associated with the outcomes of a particular
experiment or activity. An <term src="#experiment">experiment</term> is a planned operation carried out under controlled
conditions. If the result is not predetermined, then the experiment is said to be a <emphasis>chance</emphasis>
experiment. Flipping one fair coin is an example of an experiment.</para><para id="element-71">The result of an experiment is called an <term src="#outcome">outcome</term>. A <term src="#samplesp">sample space</term> is a set of all possible
outcomes. Three ways to represent a sample space are to list the possible outcomes, to
create a tree diagram, or to create a Venn diagram. The uppercase letter <m:math><m:mi>S</m:mi></m:math> is used to
denote the sample space. For example, if you flip one fair coin, <m:math><m:mi>S = {H, T}</m:mi></m:math> where <m:math><m:mi>H</m:mi></m:math> =
heads and <m:math><m:mi>T</m:mi></m:math> = tails are the outcomes.</para><para id="element-214">An <term src="#event">event</term> is any combination of outcomes. Upper case letters like <m:math><m:mi>A</m:mi></m:math> and <m:math><m:mi>B</m:mi></m:math> represent
events. For example, if the experiment is to flip one fair coin, event <m:math><m:mi>A</m:mi></m:math> might be getting at
most one head. The probability of an event <m:math><m:mi>A</m:mi></m:math> is written <m:math><m:mi>P(A)</m:mi></m:math>.</para><para id="element-544">The <term src="#prob">probability</term> of any outcome is the <emphasis>long-term relative frequency</emphasis> of that outcome.
For example, if you flip one fair coin from 20 to 2,000 times, the relative frequency of heads
approaches 0.5 (the probability of heads). Probabilities are between 0 and 1, <emphasis>inclusive</emphasis>
(includes 0 and 1 and all numbers between these values). <m:math><m:mi>P(A) = 0</m:mi></m:math> means the event <m:math><m:mi>A</m:mi></m:math> can
never happen. <m:math><m:mi>P(A) = 1</m:mi></m:math> means the event <m:math><m:mi>A</m:mi></m:math> always happens.</para><para id="element-677">To calculate the <emphasis>probability of an event <m:math><m:mi>A</m:mi></m:math></emphasis>, count the outcomes for event A and divide by the
total outcomes in the sample space. For example, if you toss a fair dime and a fair nickel, the
sample space is <m:math><m:mi>{HH, TH, HT, TT}</m:mi></m:math> where <m:math><m:mi>T</m:mi></m:math> = tails and <m:math><m:mi>H</m:mi></m:math> = heads. The sample space has four
outcomes. <m:math><m:mi>A</m:mi></m:math> = getting one head. There are two outcomes <m:math><m:mi>{HT, TH}</m:mi></m:math>. <m:math><m:mi>P(A) =  </m:mi><m:mfrac>
    <m:mn>2</m:mn>
    <m:mn>4</m:mn>
  </m:mfrac></m:math>.</para><para id="element-872"><term src="#eqlikly">Equally likely</term> means that each outcome of an experiment occurs with equal probability. For
example, if you toss a fair, six-sided die, each face (1, 2, 3, 4, 5, or 6) is as likely to occur as
any other face.</para><para id="element-189">An outcome is in the event <m:math><m:mi>A</m:mi><m:mtext> </m:mtext><m:mo>OR</m:mo><m:mtext> </m:mtext><m:mi>B</m:mi></m:math> if the outcome is in <m:math><m:mi>A</m:mi></m:math> or is in <m:math><m:mi>B</m:mi></m:math> or is in both <m:math><m:mi>A</m:mi></m:math> and <m:math><m:mi>B</m:mi></m:math>.
For example, let <m:math><m:mi>A = {1, 2, 3, 4, 5}</m:mi></m:math> and <m:math><m:mi>B = {4, 5, 6, 7, 8}</m:mi></m:math>. <m:math><m:mi>A</m:mi><m:mtext> </m:mtext><m:mo>OR</m:mo><m:mtext> </m:mtext><m:mi>B </m:mi><m:mo>=</m:mo><m:mi> {1, 2, 3, 4, 5, 6, 7, 8}</m:mi></m:math>. Notice that 4 and 5 are NOT listed twice.</para><para id="element-713">An outcome is in the event <m:math><m:mtext>A AND B</m:mtext></m:math> if the outcome is in both <m:math><m:mi>A</m:mi></m:math> and <m:math><m:mi>B</m:mi></m:math> at the same
time.

 For example, let <m:math><m:mi>A</m:mi></m:math> and <m:math><m:mi>B</m:mi></m:math> be <m:math><m:mi>{1, 2, 3, 4, 5}</m:mi></m:math> and <m:math><m:mi>{4, 5, 6, 7, 8}</m:mi></m:math>, respectively.
Then <m:math><m:mtext>A AND B</m:mtext> <m:mo>=</m:mo> <m:mo>{</m:mo><m:mn>4</m:mn><m:mo>,</m:mo><m:mn> 5</m:mn><m:mo>}</m:mo></m:math>.</para><para id="element-123">The <emphasis>complement</emphasis> of event <m:math><m:mi>A</m:mi></m:math> is denoted <m:math><m:mi>A'</m:mi></m:math> (read "A prime"). <m:math><m:mi>A'</m:mi></m:math> consists of all outcomes
that are <emphasis>NOT</emphasis> in <m:math><m:mi>A</m:mi></m:math>. Notice that <m:math><m:mi>P(A) + P(A') = 1</m:mi></m:math>. For example, let <m:math><m:mi>S = {1, 2, 3, 4, 5, 6}</m:mi></m:math>
and let <m:math><m:mi>A = {1, 2, 3, 4}</m:mi></m:math>. Then, <m:math><m:mi>A' = {5, 6}.  P(A) = </m:mi> <m:mfrac>
    <m:mn>4</m:mn>
    <m:mn>6</m:mn>
  </m:mfrac><m:mi>, P(A') = </m:mi><m:mfrac>
    <m:mn>2</m:mn>
    <m:mn>6</m:mn>
  </m:mfrac><m:mi>, and P(A) + P(A') = </m:mi><m:mfrac>
    <m:mn>4</m:mn>
    <m:mn>6</m:mn>
  </m:mfrac><m:mi> + </m:mi><m:mfrac>
    <m:mn>2</m:mn>
    <m:mn>6</m:mn>
  </m:mfrac><m:mi> = 1</m:mi></m:math> </para><para id="element-426">The <term src="#condprob">conditional probability</term> of <m:math><m:mi>A</m:mi></m:math> given <m:math><m:mi>B</m:mi></m:math> is written <m:math><m:mi>P(A|B)</m:mi></m:math>. The probability of <m:math><m:mi>A</m:mi></m:math> is
calculated knowing that <m:math><m:mi>B</m:mi></m:math> has already occurred. <emphasis>A conditional reduces the sample
space</emphasis>. We calculate the probability of <m:math><m:mi>A</m:mi></m:math> from the reduced sample space <m:math><m:mi>B</m:mi></m:math>. The formula
to calculate <m:math><m:mi>P(A|B)</m:mi></m:math> is</para><para id="element-681"><m:math><m:mi>P(A|B)=</m:mi></m:math> 
<m:math>
 <m:mfrac>
    <m:mn>P(A AND B)</m:mn>
    <m:mn>P(B)</m:mn>
  </m:mfrac>
  <m:mtext/>
</m:math></para><para id="element-400">where <m:math><m:mi>P(B)</m:mi></m:math> is greater than 0.</para><para id="element-476">For example, suppose we toss one fair, six-sided die.  The sample space <m:math><m:mi>S = {1, 2, 3, 4, 5, 6}</m:mi></m:math>. Let <m:math><m:mi>A</m:mi></m:math> = face is 2 or 3 and <m:math><m:mi>B</m:mi></m:math> = face is even (2, 4, 6). To calculate <m:math><m:mi>P(A|B)</m:mi></m:math>, we count the number of outcomes 2 or 3 in the sample space <m:math><m:mi>B = {2, 4, 6}</m:mi></m:math>. Then we divide that by the number of outcomes in <m:math><m:mi>B</m:mi></m:math> (and not <m:math><m:mi>S</m:mi></m:math>). </para><para id="element-388">We get the same result by using the formula. Remember that <m:math><m:mi>S</m:mi></m:math> has 6 outcomes.</para><para id="element-179"><m:math><m:mi>P(A|B)</m:mi><m:mo>=</m:mo></m:math> 
<m:math>
 <m:mfrac>
    <m:mtext>P(A and B)</m:mtext>
    <m:mtext>P(B)</m:mtext>
  </m:mfrac>
  <m:mtext/>
<m:mi>=</m:mi>
 <m:mfrac>
    <m:mtext>(the number of outcomes that are 2 or 3 and even in S) / 6 </m:mtext>
    <m:mtext> (the number of outcomes that are even in S) / 6 </m:mtext>
  </m:mfrac>
<m:mi>=</m:mi>
 <m:mfrac>
    <m:mn>1/6 </m:mn>
    <m:mn> 3/6 </m:mn>
  </m:mfrac>
<m:mi>=</m:mi>
 <m:mfrac>
    <m:mn>1</m:mn>
    <m:mn>3 </m:mn>
  </m:mfrac>
</m:math>
</para>   
  </content>
  

<glossary>
 


  <definition id="condprob">
    <term>Conditional Probability</term>
    <meaning>
    The likelihood that an event will occur given that another event has already occurred.
    </meaning>
  </definition>





  <definition id="eqlikly">
    <term>Equally Likely</term>
    <meaning>
    Each outcome of an experiment has the same probability.
    </meaning>
  </definition>

<definition id="experiment">
    <term>Experiment</term>
    <meaning>
  A planned activity carried out under controlled conditions.
    </meaning>
  </definition>

 <definition id="event">
    <term>Event</term>
    <meaning>
     A subset in the set of all outcomes of an experiment. The set of all outcomes of an experiment is called a <emphasis>sample space</emphasis> and denoted, as a rule, by <m:math><m:mi>S</m:mi></m:math>. An event is any arbitrary subset in <m:math><m:mi>S</m:mi></m:math>: it can contain one outcome, two outcomes, and even no outcomes (empty subset) or all of them (sample space). Standard notations for events are capital letters such as <m:math><m:mi>A</m:mi><m:mo>,</m:mo> <m:mi>B</m:mi><m:mo>,</m:mo><m:mi> C</m:mi><m:mo>,</m:mo><m:mtext> etc</m:mtext></m:math>. 
    </meaning>
  </definition>


<definition id="outcome">
    <term>Outcome (observation)</term>
    <meaning>
   A particular result of an experiment.
    </meaning>
  </definition>

 
<definition id="prob">
    <term>Probability</term>
    <meaning>
A number between 0 and 1, inclusive, that gives the likelihood that a specific event will occur. More exact, the foundation of statistics are given by the following 3 axioms (by A. N. Kolmogorov, 1930’s): Let <m:math><m:mi>S</m:mi></m:math>  denote the sample space, <m:math><m:mi>A</m:mi></m:math>  and <m:math><m:mi>B</m:mi></m:math>  are any two events in <m:math><m:mi>S</m:mi></m:math> . Then: (1). 
<m:math><m:semantics><m:mrow><m:mstyle fontsize="12pt"><m:mrow><m:mrow><m:mrow><m:mn>0</m:mn><m:mo stretchy="false">≤</m:mo><m:mi>P</m:mi></m:mrow><m:mo stretchy="false">(</m:mo><m:mi>A</m:mi><m:mrow><m:mo stretchy="false">)</m:mo><m:mo stretchy="false">≤</m:mo><m:mn>1</m:mn></m:mrow><m:mi>;</m:mi></m:mrow></m:mrow></m:mstyle><m:mrow/></m:mrow><m:annotation encoding="StarMath 5.0"> size 12{0 &lt;= P \( A \)  &lt;= 1;} {}</m:annotation></m:semantics></m:math> (2). If <m:math><m:mi>A</m:mi></m:math>  and <m:math><m:mi>B</m:mi></m:math>  are any two mutually exclusive events, then <m:math>  <m:mi>P</m:mi>
  <m:mo>(</m:mo>
  <m:mi>A</m:mi>
  <m:mi>or</m:mi>
  <m:mi>B</m:mi>
  <m:mo>)</m:mo>
  <m:mo>=</m:mo>
  <m:mi>P</m:mi>
  <m:mo>(</m:mo>
  <m:mi>A</m:mi>
  <m:mo>)</m:mo>
  <m:mo>+</m:mo>
  <m:mi>P</m:mi>
  <m:mo>(</m:mo>
  <m:mi>B</m:mi>
  <m:mo>)</m:mo>
  <m:mo>;</m:mo></m:math> (3). <m:math><m:mi>P</m:mi>
  <m:mo>(</m:mo>
  <m:mi>S</m:mi>
  <m:mo>)</m:mo>
  <m:mo>=</m:mo>
  <m:mn>1</m:mn></m:math> .
    </meaning>
  </definition>




<definition id="samplesp">
    <term>Sample Space</term>
    <meaning>
The set of all possible outcomes of an experiment.
    </meaning>
  </definition>

 


</glossary>
</document>
