This geometric probability calculator is used to find geometric distribution probability with total number of occurrence & probability … The probability mass function (pmf) of random variable $X$ is, $$ \begin{aligned} P(X=x)&=\frac{1}{6-1+1}\\ &=\frac{1}{6}, \; x=1,2,\cdots, 6. which is the probability mass function (pmf) of discrete uniform distribution. Find the value of $k$. The variance of discrete uniform distribution $X$ is, $$ \begin{aligned} V(X) &=\frac{(6-1+1)^2-1}{12}\\ &=\frac{35}{12}\\ &= 2.9167 \end{aligned} $$, A telephone number is selected at random from a directory. The probability distribution is often denoted by pm(). 1. All the integers $0,1,2,3,4,5$ are equally likely. Binomial Distribution Calculator Use this binomial probability calculator to easily calculate binomial cumulative distribution function and probability mass given the probability on a single trial, the number of trials and events. \end{aligned} $$, Mean of discrete uniform distribution $X$ is, $$ \begin{aligned} E(X) &=\sum_{x=9}^{11}x \times P(X=x)\\ &= \sum_{x=9}^{11}x \times\frac{1}{3}\\ &=9\times \frac{1}{3}+10\times \frac{1}{3}+11\times \frac{1}{3}\\ &= \frac{9+10+11}{3}\\ &=\frac{30}{3}\\ &=10. \end{aligned} $$, The variance of discrete uniform distribution $X$ is, $$ \begin{aligned} V(X) &=\frac{(8-4+1)^2-1}{12}\\ &=\frac{25-1}{12}\\ &= 2 \end{aligned} $$, c. The probability that $X$ is less than or equal to 6 is, $$ \begin{aligned} P(X \leq 6) &=P(X=4) + P(X=5) + P(X=6)\\ &=\frac{1}{5}+\frac{1}{5}+\frac{1}{5}\\ &= \frac{3}{5}\\ &= 0.6 \end{aligned} $$. a. This list has either a finite number of members, or at most is countable. Discrete uniform distribution calculator can help you to determine the probability and cumulative probabilities for discrete uniform distribution with parameter $a$ and $b$. Let the random variable $X$ have a discrete uniform distribution on the integers $0\leq x\leq 5$. Suppose $X$ denote the last digit of selected telephone number. This website uses cookies to ensure you get the best experience on our site and to provide a comment feature. Calculator of Mean And Standard Deviation for a Probability Distribution Instructions: You can use step-by-step calculator to get the mean (\mu) (μ) and standard deviation (\sigma) (σ) associated to a discrete probability distribution. \end{aligned} $$, eval(ez_write_tag([[250,250],'vrcacademy_com-banner-1','ezslot_9',127,'0','0']));a. Discrete Random Variable Calculator Online probability calculator to find expected value E (x), variance (σ 2) and standard deviation (σ) of discrete random variable from number of outcomes. 4 of theese distributions are available here. Hope you like article on Discrete Uniform Distribution. This list has either a finite number of members, or at most is countable. c. Find the probability that $X\leq 6$. (adsbygoogle = window.adsbygoogle || []).push({}); Discrete probability distributions arise in the mathematical description of probabilistic and statistical problems in which the values that might be observed are restricted to being within a pre-defined list of possible values. Code to add this calci to your website Discrete Random Variable's expected value,variance and standard deviation are calculated easily. The probability mass function of $X$ is, $$ \begin{aligned} P(X=x) &=\frac{1}{9-0+1} \\ &= \frac{1}{10}; x=0,1,2\cdots, 9 \end{aligned} $$, a. a. Some Examples include 'chance of three random points on a plane forming an acute triangle', 'calculating mean area of polygonal region formed by random oriented lines over a plane'. $P(X=x)=k$ for $x=4,5,6,7,8$, where $k$ is constant. \end{aligned} $$, $$ \begin{aligned} E(X^2) &=\sum_{x=0}^{5}x^2 \times P(X=x)\\ &= \sum_{x=0}^{5}x^2 \times\frac{1}{6}\\ &=\frac{1}{6}( 0^2+1^2+\cdots +5^2)\\ &= \frac{55}{6}\\ &=9.17. The probability that the last digit of the selected number is 6, $$ \begin{aligned} P(X=6) &=\frac{1}{10}\\ &= 0.1 \end{aligned} $$, b. Roll a six faced fair die. A random variable $X$ has a probability mass function The calculator can also solve for the number of trials required. The probability that the last digit of the selected telecphone number is less than 3, $$ \begin{aligned} P(X < 3) &=P(X\leq 2)\\ &=P(X=0) + P(X=1) + P(X=2)\\ &=\frac{1}{10}+\frac{1}{10}+\frac{1}{10}\\ &= 0.1+0.1+0.1\\ &= 0.3 \end{aligned} $$, c. The probability that the last digit of the selected telecphone number is greater than or equal to 8, $$ \begin{aligned} P(X\geq 8) &=P(X=8) + P(X=9)\\ &=\frac{1}{10}+\frac{1}{10}\\ &= 0.1+0.1\\ &= 0.2 \end{aligned} $$. Step 4 - Click on âCalculateâ for discrete uniform distribution, Step 6 - Calculate cumulative probabilities. You can refer below recommended articles for discrete uniform distribution theory with step by step guide on mean of discrete uniform distribution,discrete uniform distribution variance proof. All the numbers $0,1,2,\cdots, 9$ are equally likely. $$ \begin{aligned} E(X^2) &=\sum_{x=9}^{11}x^2 \times P(X=x)\\ &= \sum_{x=9}^{11}x^2 \times\frac{1}{3}\\ &=9^2\times \frac{1}{3}+10^2\times \frac{1}{3}+11^2\times \frac{1}{3}\\ &= \frac{81+100+121}{3}\\ &=\frac{302}{3}\\ &=100.67. \end{aligned} $$, Let $Y=20X$. Thus the random variable $X$ follows a discrete uniform distribution $U(0,9)$. If we consider to be a random variable that takes the values then the uniform distribution would assign each value a probability … Let $X$ denote the last digit of randomly selected telephone number. b. 4. 1. \end{aligned} $$, $$ \begin{aligned} V(X) &= E(X^2)-[E(X)]^2\\ &=9.17-[2.5]^2\\ &=9.17-6.25\\ &=2.92. 2. Let the random variable $Y=20X$. Below are the few solved examples on Discrete Uniform Distribution with step by step guide on how to find probability and mean or variance of discrete uniform distribution. The Discrete uniform distribution, as the name says is a simple discrete probability distribution that assigns equal or uniform probabilities to all values that the random variable can take. Find the probability that the last digit of the selected number is, eval(ez_write_tag([[728,90],'vrcacademy_com-large-mobile-banner-2','ezslot_13',121,'0','0']));a. c. The mean of discrete uniform distribution $X$ is, $$ \begin{aligned} E(X) &=\frac{1+6}{2}\\ &=\frac{7}{2}\\ &= 3.5 \end{aligned} $$ Using the Binomial Probability Calculator For variance, we need to calculate $E(X^2)$. A discrete random variable $X$ is said to have uniform distribution with parameter $a$ and $b$ if its probability mass function (pmf) is given byeval(ez_write_tag([[580,400],'vrcacademy_com-medrectangle-3','ezslot_4',126,'0','0'])); $$f(x; a,b) = \frac{1}{b-a+1}; x=a,a+1,a+2, \cdots, b $$, $$P(X\leq x) = F(x) = \frac{x-a+1}{b-a+1}; a\leq x\leq b $$, The expected value of discrete uniform random variable $X$ is, The variance of discrete uniform random variable $X$ is, A general discrete uniform distribution has a probability mass function, Distribution function of general discrete uniform random variable $X$ is, The expected value of above discrete uniform random variable $X$ is, The variance of above discrete uniform random variable $X$ is. Continuous Uniform Distribution Calculator, Weibull Distribution Examples - Step by Step Guide, Karl Pearson coefficient of skewness for grouped data. 3. To analyze our traffic, we use basic Google Analytics implementation with anonymized data. As the given function is a probability mass function (pmf), we have, $$ \begin{aligned} & \sum_{x=4}^8 P(X=x) =1\\ \Rightarrow & \sum_{x=4}^8 k =1\\ \Rightarrow & k \sum_{x=4}^8 =1\\ \Rightarrow & k (5) =1\\ \Rightarrow & k =\frac{1}{5} \end{aligned} $$, Thus the probability mass function (pmf) of $X$ is, $$ \begin{aligned} P(X=x) =\frac{1}{5}, x=4,5,6,7,8 \end{aligned} $$. Geometric Distribution \end{aligned} $$, And variance of discrete uniform distribution $Y$ is, $$ \begin{aligned} V(Y) &=V(20X)\\ &=20^2\times V(X)\\ &=20^2 \times 2.92\\ &=1168. Determine mean and variance of $X$. Use beelow discrete uniform distribution calculator to find probability and cumulative probabilities. Discrete Distributions Calculators HomePage Discrete probability distributions arise in the mathematical description of probabilistic and statistical problems in which the values that might be observed are restricted to being within a pre-defined list of possible values. Determine mean and variance of $Y$. c. Compute mean and variance of $X$. The probability that the number appear on the top of the die is less than 3 is, $$ \begin{aligned} P(X < 3) &=P(X=1)+P(X=2)\\ &=\frac{1}{6}+\frac{1}{6}\\ &=\frac{2}{6}\\ &= 0.3333 \end{aligned} $$ So p ()1 =PM()=1= 1 3, p()2 = 1 2, p()3 = 1 6. 6. The probability distribution of a discrete random variable X is a listing of each possible value x taken by X along with the probability P(x) that X takes that value in one trial of the experiment. \end{aligned} $$. Let $X$ denote the number appear on the top of a die.

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