Calculating marginal distribution Contact your hosting provider for more information. In this informative video, we will Marginal distributions AP. Sep 30, 2025 · This comprehensive, step-by-step guide is meticulously crafted to demystify Marginal Distribution, providing you with the clarity and practical tools needed to master its calculation and confidently apply it in your data analysis endeavors. For a particular value of x, add up over all possible values of y. Problem calculating joint and marginal distribution of two uniform distributions Ask Question Asked 14 years, 9 months ago Modified 7 years, 1 month ago Dec 2, 2016 · As usual, I tried to find the marginal PDF of X by $$\int_ {0}^ {1}f (x,y) dy $$ However, this gives me 1. Oct 16, 2019 · If you're unsure about the marginal distribution statistics definition in a two-variable problem, you're really just pretending the other variable doesn't exist. I'm sure there is an easy way, however I can not seem to find a function for it. We have been studying such distributions in the earlier chapters on univariate variables. Here's a picture from the book where this exercise is from (https://mml-book. Estimate annual RMD, tax impact, and remainin 9 There will be many different distributions with the same marginal distributions, so one needs to select a specific way to aggregate the marginal distributions into joint distributions. Jan 27, 2025 · How To Calculate Marginal Distribution In Statistics? Understanding how to calculate marginal distribution is key when analyzing data with multiple variables. Mar 4, 2021 · [1 In the question I know how to calculate marginal distribution for X1 and X2. A Federal Income Tax Calculator is a free financial tool that helps you calculate your federal income tax liability based on the latest 2025 IRS tax brackets and rates. Distribution Calculator This distribution calculator determines the Cumulative Distribution Function (CDF), scores, probabilities between two scores, and PDF or PMF for the following distributions: Normal, Binomial, Student's t, F, Chi-Square, Poisson, Weibull, Exponential, and Uniform. A marginal probability distribution is the probability distribution of a subset of a collection of random variables. It is used to identify the most important variables in a dataset and to assess the impact of a single variable on the overall dataset. 1 Joint PDFs and Expectation The joint continuous distribution is the continuous counterpart of a joint discrete distribution. Math: HSS. The method used depends on the type of variables involved. Historical Background The use of marginal Dec 27, 2018 · You can calculate it from the joint distribution by summing up over all values of y (using the usual formula you know). This is the called the frequentist paradigm of statistical inference. This concept is essential for understanding how different discrete random variables . That definition sounds a bit convoluted, but the concept is simple. A multinomial distribution is a closed form function that answers the question: What is the probability that there are ci trials with Understanding marginal distributions is essential for statistical analysis, as they form the basis for calculating conditional probabilities and assessing relationships between variables. Nov 10, 2021 · A guide to correctly calculating posterior predictions and average marginal effects with multilievel Bayesian models How to calculate grand means, conditional group means, and hypothetical group means of posterior predictions from multilevel brms models. It's fundamental for understanding the relationship between two variables by highlighting the overall distribution across categories. Marginal distribution and conditional distribution. We investigate distributions using a two-way table and then explain the concept of marginal distribution, both in counts and percentages, to understand the distribution of each variable individually. In this article, we will explore marginal probability, the marginal probability formula and how to determine the marginal probability of discrete and continuous variables. Find $P (X \leq 2, Y \leq 4)$. All of the marginal probabilities are shown in Worksheet 5. What is Marginal Distribution? Marginal distribution is a fundamental concept in statistics that describes the probability distribution of a subset of variables within a larger multivariate distribution. It plays a crucial role in the analysis of data across diverse fields, allowing researchers to understand individual probability distributions independently of joint distributions with other variables. The formula for calculating marginal density is: The first two conditions in Definition 5. For another explanation of marginal and conditional distributions, watch this YouTube video: It is called a marginal probability when we are looking at any of the marginal sums divided by the grand total in a cross-classification table. 5 (Conditional distribution of the number of B alleles) Suppose that the A gene codes for a visible trait, such as albinism, while the B gene codes for an invisible trait, such as Tay-Sachs disease (which typically does not manifest until age three). Jun 11, 2025 · Calculating marginal distribution involves integrating or summing out the other variables in a multivariate distribution. 2 in rows 12 to 18 of the same Excel Worksheet. Find $P (Y Marginal distributions represent the probabilities of each individual variable in a joint distribution, disregarding the influence of other variables. 8 Marginal distributions Even when outcomes of a random phenomenon are equally likely, values of related random variables are usually not. 5. Use the Distribution type section to select what distributions you would like to be displayed Use the Variable Settings section to input the distribution parameters and correlation coefficient Use the Control section to input appropriate bivariate limits for X and Y variables Use the Graph Settings sections to indicate what type of Marginal Distribution and Joint Bivariate Distribution to view Calculating variance of marginal distribution Ask Question Asked 11 years ago Modified 11 years ago Sep 21, 2024 · We go over how to use a two-way table to calculate a marginal distribution in percents. Therefore, conceptual ideas and formulas will be roughly similar to that of discrete ones, and the transition will be much like how we went from single variable discrete RVs to continuous ones. We’ll also see the concept of dependent and independent events. Like for X1 the marginal distribution for each column is the sum of each joint probability mass function in that colu Example problem on how to find the marginal probability density function from a joint probability density function. What is a Marginal Distribution? A A conditional distribution lists the relative frequency of each category of variable, given a specific value of the other variable in the contingency table. Jul 23, 2025 · Marginal Probability is a fundamental concept in probability theory and statistics. We used two-way tables in Chapters 1 and 2 to calculate marginal and conditional distributions. Remark: Suppose X, Y are independent. Learn how to calculate marginal distribution. Aug 31, 2024 · Calculate the marginal distribution of dogs by dividing the total number of dogs by the total number of animals and multiplying by 100 to convert it into a percentage. We will see many ways of describing a distribution, depending on how many random variables conditional distribution ≡ marginal distribution. Specifically, the probability that I make 2 unforced errors in a game is the probability that I make 2 and Esther makes 0 + the probability that I make 2 and Esther makes 1 + . 1 provide the requirements for a function to be a valid joint pdf. Sep 13, 2023 · We disregard the occurrence of a second event while calculating marginal distribution. It is a method used to determine the probability distribution of a single variable by examining its relationship with multiple variables in a joint distribution. Calculate the marginal distributions for each of the variables in a two-way table of counts. Discrete joint distributions For two discrete joint random variables and , the joint probability mass function is defined as: , , = = , = The marginal distributions of the joint PMF are defined as: 5 = = = . Then you give the complete distribution of the variable that still "exists. 4. In this video we will use StatCrunch to finding the Marginal Distributions of a Contingency Table as well as The Relative Frequency Marginal Distributions. The BVN2 version provides more accurate estimates of the Bivariate Normal Distribution probability calculation and relies on the modern 3D Plotly visualization. Since we already have joint posterior above, it makes sense to marginalize it as shown; Jul 17, 2019 · In this article, we’ll cover marginal and conditional probability for discrete and continuous variables.  … The distribution of an individual random variable is call the marginal distribution. Learn how to calculate and apply it in real-world scenarios. d: Multivariate Random Variables – Calculate variance and standard deviation for conditional and marginal probability distributions for discrete random variables only. The reason for using the word “marginal” will become clear as soon as we see the output. I want to know the corresponding marginal densities. A marginal distribution is a distribution of values for one variable that ignores a more extensive set of related variables in a dataset. Worksheet 5. Jul 23, 2024 · For a joint distribution of two random variables, X and Y, represented as P (X, Y), the marginal distribution of X is found by summing P (X, Y) over all possible values of Y: May 27, 2025 · Explore the concept of marginal distribution in probability theory, its properties, and its far-reaching implications in various fields. 1 Informally, we can think of a conditional probability distribution as a probability distribution for a sub-population. In other words, a conditional probability distribution describes the probability that a randomly selected person from a sub-population has a given characteristic of interest. " Marginal probability takes into account the one variable. So my point is: which function in Python does that? Practice calculating marginal distributions in two-way tables. Marginal distributions give the probability distribution of a subset of random variables while ignoring the other variables in the joint distribution. What is different? Dec 21, 2020 · This tutorial provides a simple introduction to joint probability distributions, including a definition and several examples. It gives their de nitions in terms of prob-abilities, and a few simple examples. Sometimes referred to as the "marginals" because they are the information at the margins of a table. The former is an algorithm to calculate the marginal likelihood from the posterior draws of the Gibbs sampling algorithm, and the latter calculates the marginal likelihood from the posterior draws of the Metropolis-Hastings algorithm. Q (LO), UNC‑1. STATS: UNC‑1 (EU), UNC‑1. In the field of statistics and probability, marginal distribution plays a critical role in understanding the behavior of variables. khanacademy. The SOCR Trivariate Normal (TVN) Probability Calculator provides an approximation to the joint 3D probability distribution of 3 marginal distributions. Difference between conditional distribution and a marginal distribution. The previous lecture covered probability distributions, random vectors, Gaussian distributions and their transformations, expectations and covariance. In both images I have plotted one thousand samples drawn from the underlying joint distribution. May 2, 2020 · Calculating marginal distribution from Discrete Joint Probability Distribution Asked 4 years, 10 months ago Modified 4 years, 10 months ago Viewed 511 times Oct 2, 2020 · Marginal Distribution Formula For Discrete So, for discrete random variables, the marginals are simply the marginal sum of the respective columns and rows when the values of the joint probability function are displayed in a table. The marginal distribution tells us about the behaviour of one random variable alone, i. This means that, for example, we can obtain PMF of $X$ from its joint PMF with $Y$. This lecture covers marginal distributions, conditional distributions and joint distributions in the context of transformations on vectors in control and estimation problems. 2 5 1 3 5 1 3 5 1 2 Link to Video: Independent Random Variables In this chapter we consider two or more random variables defined on the same sample space and discuss how to model the probability distribution of the random variables jointly. 1, the joint cd f for continuous random variables X and Y is obtained by integrating the joint density function over a set A of the form A Sep 10, 2019 · 2 Neither the marginal distributions, nor the joint distributions are normal. Oct 2, 2024 · Marginal frequency is a concept used in statistics to describe the sum of probabilities or frequencies across a row or column in a contingency table, providing insight into the distribution of variables within a dataset. It provides the total probability of event occurrence. Learn what marginal probability is, how to calculate it, and see worked examples for both discrete and continuous variables. These tables organize data in a way that supports the calculation of relative frequency and, therefore, experimental (empirical) probability. Jan 23, 2013 · How to find marginal distribution from joint distribution with multi-variable dependence? Ask Question Asked 12 years, 10 months ago Modified 3 years, 8 months ago Oct 3, 2014 · I came across a problem where the marginal distribution of a random variable $Y$, $f (y) = c/y^2$ and $f (x|y) = 1/y$. In probability theory and statistics, the multivariate normal distribution, multivariate Gaussian distribution, or joint normal distribution is a generalization of the one-dimensional (univariate) normal distribution to higher dimensions. 5 Google Classroom You might need: Calculator Here is a table giving the number of US households (in thousands) in 2013 by tenure and insurance status: Study with Quizlet and memorize flashcards containing terms like What is a Two-Way Table?, What number is always used when calculating marginal distributions?, You are given a graph comparing the rates of different Races of Suspects to different Force Levels. Assuming they are independent is essentially making one of these possible choices. We will begin with the discrete case by looking at Free RMD calculator to calculate required minimum distributions from retirement accounts using 2025 IRS tables. Apr 16, 2016 · I am not able to show why the marginal probability of this distribution, with respect to either $x_1$ or $x_2$ follows $b (n, p_1)$ or $b (n, p_2)$, respectively. org/math/ap-st StatsResource. 5 in the textbook. Using the margin of the two way table we can see the total counts for a categorical variable, not subject to Aug 25, 2015 · I know the marginal distribution to be the probability distribution of a subset of values, does that mean the marginal distribution can be obtained by calculating the probability distribution of the piecewise function in locations where $f (x, y)$ does not equal zero? Probabilities may be either marginal, joint or conditional. e. Example 13. Let’s calculate a conditional distribution from the joint distribution. We explain its formula, examples, and differences with conditional and joint probabilities. Oct 8, 2015 · 2. Define Xi to be the number of trials with outcome i. Mar 29, 2017 · I would like to calculate the marginal probability distributions from a dataframe containing raw binary data. 3. In order to understand how to calculate marginal distribution in Excel, let's walk through a sample dataset and apply the steps needed to perform this calculation. Then for any functions g and h, g(X ) and h(Y ) are also independent Remark: Two continuous random variables are independent if and only if its density f (x, y) can be written in split-form of f (x, y) = g(x)h(y). Guide to what is Marginal Probability. To memorise this concept, remember that Computes the marginal distribution of a set of variables in R. 3. They are obtained by integrating the joint density function over the other variables. See Theorem 5. This document is an introduction to entropy and mutual information for discrete random variables. A marginal distribution is the distribution of the row variable alone or of the column variable alone. For instance, while calculating the marginal distribution of students who obtained a C with respect to the total number of students, we simply sum the number of students for each class across the row and dice the value with the total number of students. May 27, 2025 · Explore the concept of marginal distribution in probability theory, its properties, and its far-reaching implications in various fields. github. Find the marginal PMFs of $X$ and $Y$. 1. The three approaches will be reviewed, compared, and contrasted in relation to various joint probability structures frequently encountered in 8 Covariance and Correlation Consider the two multivariate distributions shown bellow. Feb 11, 2025 · Marginal Probability If a probability is computed using only totals in the margins from the table (the far right column, or the bottom row in the above table), it is called a marginal probability. 5 which is greater than 1. The (probability) distribution of a collection of random variables identifies the possible values that the random variables can take and their relative likelihoods. In a joint probability distribution involving multiple random variables, the marginal Marginal probability distribution is then obtained by summing or integrating these joint probabilities over the unwanted variable (s). Ask Question Asked 7 years, 7 months ago Modified 7 years, 7 months ago 12 Marginal Distributions Given the joint distribution of (X,Y) (X, Y) we may want to find the (marginal) distribution of X X or Y Y alone. We’ll introduce the math smoothly with Python and drawings. Given a known joint distribution of two discrete random variables, say, X and Y, the marginal distribution of either variable – X for example – is the probability distribution of X when the values of Y are not taken into consideration. I just want to know P{X = i}. Discrete probability distributions are appropriate when dealing with countable values, while continuous probability distributions are suitable for variables with infinite possibilities. io/): I agree with @heropup approach of calculating marginal distributions analytically. 2. In this context, the distribution of one of the variables alone is called a marginal distribution. . This calculator works for: Tax planning - Estimate federal tax liability before Dec 18, 2017 · Calculate marginal distribution, P(X = 0|Y> 0) P (X = 0 | Y> 0), expected value and variance. Note the asymmetric, narrow ridge shape of the PDF – indicating that small values in the X dimension are more likely to occur when small values in the Y dimension occur. Aug 29, 2023 · To read more on the topic of Joint Probability, you can read the linked article. Visual representations like histograms or density plots can help illustrate the marginal distribution of y, making it easier to interpret and analyze. Thanks for watching!! ️Tip Jar 👉🏻👈🏻 ☕ Index: The Book of Statistical Proofs Probability Distributions Multivariate continuous distributions Multivariate normal distribution Marginal distributions Theorem: Let x x follow a multivariate normal distribution: x ∼ N (μ,Σ). Understanding their differences and how to manipulate among them is key to success in understanding the foundations of statistics. Let Z1; Z2 (0; 1), which we will use to build a general bivariate normal distribution. Given a two-way table of counts, calculate the conditional distribution of one variable for each level of the other variable. Feb 28, 2012 · Abstract Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo-) based approaches to the calculation of numerical estimates of marginal probability distributions. For calculating marginal distributions in discrete random events given in tabular format, we may also add up the probabilities in the columns and rows and obtain: This video provides a list of probability formulas that can help you to calculate marginal probability, union probability, joint probability, conditional pro Feb 15, 2021 · Learn how to use information in contingency tables to calculate joint, marginal, and conditional probabilities. Later on, we will use contingency tables again, but in another manner. Mar 13, 2024 · Marginal probability, a fundamental concept in statistics, refers to the probability of an event occurring without consideration of other variables. Q. This calculator works for: Tax planning - Estimate federal tax liability before Marginal Probability Distribution Finder Marginal Probability Distribution Finder X Values (comma-separated): Y Values (comma-separated): Joint Probabilities (comma-separated for each pair): Calculate Marginal Probabilities Marginal Probability Distribution: X Values P (X) Y Values P (Y) Download PDF Dec 18, 2017 · Calculate marginal distribution, P(X = 0|Y> 0) P (X = 0 | Y> 0), expected value and variance. The marginal probability of X is the probability that a randomly selected person makes a certain number of credit card purchases per week, for example PX(2) = the probability that a randomly selected person makes 2 credit card purchases per week, This Account has been suspended. Table of contents 5 1 1 5 1 2 5 1 1 X Y X Y X Y 5 1 1 5 1 2 Link to Video: Walkthrough of Example 5. The components of marginal revenue 4. The joint distribution of random variables \ (X\) and \ (Y\) (defined on the same probability space) is a probability distribution on \ ( (x, y)\)pairs. Nov 19, 2020 · My question is regarding calculation of marginal posterior distribution, $p (\sigma^ {2}|y)$. Stochastic substitution, the Gibbs sampler and the sampling-importance-resampling algorithm can be viewed as three alternative sampling, or Monte Carlo, based approaches to the calculation of numerical estimates of marginal probability distributions. Lecture 20 | Bayesian analysis Our treatment of parameter estimation thus far has assumed that is an unknown but non-random quantity|it is some xed parameter describing the true distribution of data, and our goal was to determine this parameter. It is obtained by averaging or summing the joint probability distribution of all variables in the collection, effectively 'removing' or 'marginalizing out' the other variables. Specifically, it refers to the probabilities of each variable occurring independently of the others. Calculate the marginal Feb 11, 2025 · Marginal Probability If a probability is computed using only totals in the margins from the table (the far right column, or the bottom row in the above table), it is called a marginal probability. Use the Distribution type section to select what distributions you would like to be displayed Use the Variable Settings section to input the distribution parameters and correlation coefficient Use the Control section to input appropriate bivariate limits for X and Y variables Use the Graph Settings sections to indicate what type of Marginal Distribution and Joint Bivariate Distribution to view Sep 5, 2024 · To calculate a marginal distribution, you simply sum or integrate out the other variables from the joint distribution, leaving you with the probability distribution of the variables of interest. 12 would be verbalized as "nought point one two" Computing the marginal distributions, and expected values. Finally, we cover conditional distribution, where we look at the relationship between variables and understand how one variable impacts the distribution of another. Dec 21, 2020 · This tutorial provides a quick introduction to marginal distributions, including a definition and examples. The most common way to make the choice, is by working with a copula. The different races are Black, Hispanic, and White. 1 (EK) CCSS. View more lessons or practice this subject at http://www. Learn how to create marginal distributions, and see examples that walk through sample problems step-by-step, for you to improve your statistics knowledge and skills. Jul 23, 2025 · To find a marginal distribution from a joint distribution, you essentially sum or integrate over the variables that you are not interested in. ID. 3 is a copy of Worksheet 5. The Marginal probabilities are essential for understanding joint distributions and are commonly used in various fields including economics, engineering and social sciences. Profit maximization and loss minimization BYOB is a monopolist in beer production and distribution in the imaginary economy of Hopsville. Let’s say I don’t care about Y . 5,8 , Oct 6, 2023 · Marginal Distributions and Joint Densities Marginal distributions describe the probability distribution of a single variable in a joint distribution, ignoring the other variables. Calculating Marginal Probability Distribution The calculation of marginal probability distribution can be performed using two primary methods: summation for discrete variables and integration for continuous Jun 13, 2025 · Unlock the secrets of marginal distribution in discrete probability. Given the joint distribution of X and Y , we sometimes call distribution of X (ignoring Y ) and distribution of Y (ignoring X ) the marginal distributions. In this post, we’ll explore the concept of marginal distributions—what they mean, why they matter, and how to compute them using clear examples, visuals, and practical exercises. To calculate the marginal distributions, we just add up over values of the other random variable. io | Joint Random Variables - Marginal Distributions The discrete random variables X and Y have a joint distribution given in the presentation. Calculate marginal distribution in Sourcetable with ease, simplifying complex data analysis. You can imagine looking at the joint probability function in (say) the x x -direction, and accumulating the probability in that direction. The three approaches will be reviewed, and compared and contrasted, in relation to various joint probability structures frequently encountered in May 18, 2025 · Marginal distributions offer insights into the behavior of a single variable regardless of the other. In this and the next lecture, we will describe an alternative Bayesian paradigm The joint PMF contains all the information regarding the distributions of $X$ and $Y$. How do I find the marginal density function for X? I think I need to integrate $f_ {X,Y} (x,y)$ over $dy$ but what do I integrate it from? Should it be 0 and 1 or 0 and x or x and 0? I've looked over a lot of examples with different domains but I can't figure out their method in getting the range for integration. Probability distributions provide a valuable framework for understanding and analyzing uncertainty in statistical contexts. Continue to help good content that is interesting, well-researched, and useful, rise to the top! To gain full voting privileges, Practice calculating marginal distributions in two-way tables. irrespective of the other. It refers to the probability of the single event occurring irrespective of the outcomes of the other related events. The marginal mass function for X is found by summing over the appropriate column and the marginal mass function for Y can be found be summing over the appropriate row. Marginal Probability Distributions (continuous) May 18, 2025 · Welcome to our comprehensive AP Stats Marginal Distribution Tutorial. As an example of applying the third condition in Definition 5. Marginal Distribution in Statistics Marginal distributions are a key concept in statistics and data analysis, particularly in the study of probability distributions. The marginal distribution of a continuous random variable can be described by a probability density function, for which areas under the density curve determine probabilities. Can I simply multiply these two to get $f (x,y)$ the joint distribution of $X$ and $Y$, which in this case will be $c/y^3$. Mar 1, 2013 · Let $ (X, Y)$ have a normal distribution with mean $ (\mu_X, \mu_Y)$, variance $ (\sigma_X^2, \sigma_Y^2)$ and correlation $\rho$. 4 Marginal distributions A marginal distribution can be found by ‘integrating out’ (in the continuous case) the other variables. They are derived by summing or integrating the joint probabilities over the other variables, providing insights into the behavior of individual random variables. Calculating marginal revenue from a linear demand curve The blue curve on the following graph represents the demand curve facing a firm that can set its own prices. B. Jul 23, 2025 · To calculate the marginal probability in the probability distribution table, add the rows or columns of the required variable. Marginal distribution is a statistical concept that describes the distribution of a single variable in a dataset. How can I approach the problem? 3 Multinomial Distribution Say you perform n independent trials of an experiment where each trial results in one of m outcomes, with respective probabilities: p1; p2;:::; pm (constrained so that åi pi = 1). Jan 17, 2013 · Important - In UK and Ireland We often say "Nought" when referring to the number "0" 0. Clearly the two distributions are different. Marginal Distribution of X # To find the numerical values of the distribution of X, we will use a method called marginal that operates on a joint distribution object and takes the variable name as its argument. 2. This guide is designed especially for AP Statistics students and educators seeking clarity on this important topic. Conditional distributions allow us to assess how the probability of one variable changes given the value of another. , n} then we can view Ai,j = P{X = i, Y = j} as the entries of an n × n matrix. It determines your total tax owed, effective tax rate, marginal tax rate, and after-tax income based on your annual income and filing status. What is Marginal Practice calculating marginal distributions in two-way tables. Problem Consider two random variables $X$ and $Y$ with joint PMF given in Table 5. Jun 28, 2019 · Topic 3. Oct 9, 2020 · I wish to calculate the marginal CDF of a joint probability distribution function. Marginal Distribution definition, formula and examples using a frequency table. Probability Distribution and Marginal Distribution Probability Distribution In explaining the possibility of various outcomes happening in a random experiment or process, a key idea in probability theory is the probability distribution. Given a two-way table of counts, calculate the joint distribution of the two variables. This article delves into the definition of marginal distributions, provides practical examples, explains their importance in statistical analysis, and discusses their role in data science. If X and Y assume values in {1, 2, . However, the mean and variance are the same in both the x and the y dimension. Stochastic substitution, the Gibbs sampler, and the sampling-importance-resampling algorithm can be viewed as three alternative sampling- (or Monte Carlo- ) based approaches to the calculation of numerical estimates of marginal probability distributions. (1) (1) x ∼ N (μ, Σ) Then, the marginal distribution of any subset vector xs x s is also a multivariate normal distribution xs ∼ N (μs,Σs) (2) (2) x s Link to Video: Walkthrough of Example 5. The third condition indicates how to use a joint pdf to calculate probabilities. However, I am unsure of the bounds I am supposed to use, and wish to verify it. uqcw hcnnwvm klqh gee ngzl vejodz vlioji eblsyf xjtffc uvue xnll mux wve zowj uujr