Variance of sampling distribution. Add all data values and divide by the sample size n.

An airline claims that 72% 72 % of all its flights to a certain region arrive on time. m(m + 1) (2m + 1)2 × 2(m + 1) = m 2(2m + 1)2 ∼ 1 8m. 2 minutes, Standard deviation = 8 minutes 2) Find z-score for 43 minutes: z = (43 - 46. For an infinite population, the variance depends only on the population variance and sample size. The variance is 11. The population is infinite, or. standard deviation of the sampling distribution of x̄ 1 - x̄ 2 c. Happy learning! Sampling distribution of the sample mean. E (S2)= Compare E (S2) to σ2. . Then E( y ) = 100 0. The formula to calculate population variance is: σ2 = Σ (xi – μ)2 / N. Distribution of sample variance from normal distribution. Jan 16, 2010 · When the sample size n is small, the random variable T = n(x -μ)/S is said follow a central t distribution with degrees of freedom (n -1), where X is the sample mean and S is the sample standard Feb 9, 2021 · ‼️statistics and probability‼️🟣 grade 11: finding the mean and variance of the sampling distribution of sample mean ‼️shs mathematics playlist‼️general math 6: Sampling Distributions. 9037 \end {equation} There is a 90. The second video will show the same data but with samples of n = 30. iances and covariances4. $\begingroup$ @moldovean About as to why $(n−1)S^2/\sigma^2$ is a Ki2 distribution, I see it this way : $\sum(x_i-\overline{x})^2$ is the sum of the square value of N variables following normal distribution with expected value 0 and variance $\sigma^2$. This is a application of Corollary 6. Aug 26, 2021 · yn = β0 +β1xn,1 +⋯+ βP xn,P +εn. However, sampling distributions—ways to show every possible result if you're taking a sample—help us to identify the different results we can get from repeated sampling, which helps us understand and use repeated samples. Part 2: Find the mean and standard deviation of the sampling distribution. The document discusses the properties of the sampling distribution of sample means when samples of different sizes are drawn from a population. Add all data values and divide by the sample size n. The sample variances target the value of the population variance. All the summation is from 1 to N. 2 - Sampling Distribution of Sample Mean; 26. Apr 26, 2021 · This video lesson is about computing the mean and the variance of the sampling distribution of the sample means. In this paper we introduce a novel method that allows us to exactly determine all the characteristics of a PSO sampling distribution and explain how it changes over any number of generations, in the presence stochasticity. Now that we've got the sampling distribution of the sample mean down, let's turn our attention to finding the sampling distribution of the sample variance. Is Remy's claim correct? 1. 0. Using variance we can evaluate how stretched or squeezed a distribution is. 55,199) = 0. Variance of a sample proportion is given by the formula [1]: Where: p = true proportion of population individuals with the property. Calculate the variance. Total 𝐀 𝐀 = 1. Now you can map your iid uniform to iid Gaussian using the inverse distribution about the mean and the variance of the sampling distribution of the sample means. While the sampling distribution of the mean is the most common type, they can characterize other statistics, such as the median, standard deviation, range, correlation, and test statistics in hypothesis tests. where μx is the sample mean and μ is the population mean. We will use these steps, definitions, and formulas to calculate the Sampling distribution. Oct 8, 2018 · This distribution of sample means is known as the sampling distribution of the mean and has the following properties: μx = μ. Interquartile range: the range of the middle half of a distribution. Question A (Part 2) 26. Χ = each value. Jan 6, 2020 · Sampling Distributions • If we conduct the same experiment several times with the same sample size, the probability distribution of the resulting statistic is called a sampling distribution • Sampling distribution of the mean: if n observations are taken from a normal population with mean μ and variance σ2, then: JMB 2018 2019 Sep 26, 2012 · I have an updated and improved (and less nutty) version of this video available at http://youtu. Use σ x ¯ = σ n whenever. define the sampling distribution of the sample mean for normal. The proportion variance is the variance in all variables that is accounted for by a As observed in the above example, the sampling distribution of the sample variances is an asymmetric distribution with many small sample variances and a few large sample variances. Feb 2, 2022 · Sampling Variance. - The central limit theorem states that sampling distributions of sample means will be approximately normally distributed regardless of Here are the step-by-step workings: 1) Given: Mean = 46. The mean of the sampling distribution is very close to the population mean. Its formula helps calculate the sample’s means, range, standard deviation, and variance. n= 5: E (Xˉ)=μ (b) Determine the sampling distribution of the sample variance S2. The mean score in a class of 30, will have lower variance than the variance of a single individual, in fact $\sigma^2/30$. I derive the mean and variance of the sampling Rule of Thumb. Input the sample data (n = 7, X = 160). A random sample of 100 employees was selected and surveyed about employee satisfaction. Modified 9 years, 7 months ago. To do this, we need to make some assumptions. Ask Question Asked 9 years, 7 months ago. 3 shows all possible outcomes for the range of two numbers (larger number minus the smaller number). The form of the sampling distribution of the sample mean depends on the form of the population. \ (X_1, X_2, \ldots, X_n\) are observations of a random sample of size \ (n\) from The probability will be the area under the chi-square distribution between these values. A population is a group of people having the same attribute used for random sample collection in terms of Module 5 Lesson 4 Mean and Variance of the Sampling Distribution of Sample Means - Free download as PDF File (. The sampling distributions are: n= 1: x-01P(x-)0. 3 - Sampling Distribution of Sample Variance; 26. Write the distribution in proper notation, and calculate the theoretical mean and standard deviation. The distinction between sample mean and population mean is also clarified. Let Z be the value you get from sample with sample size 1. 1 OverviewThe expected value of a random variable gives a crude measure for the \center of location" of the d. Hence state and verify relation between (a). For a sample size of more than 30, the sampling distribution formula is given below – Mar 14, 2020 · Stack Exchange Network. where Zi is the random variable, = 1 if Yi is Jan 18, 2023 · When you collect data from a sample, the sample variance is used to make estimates or inferences about the population variance. Subject Matter: Sampling Distribution of the Sample Means from an Infinite Population Grade Level: XII Time Allotment: 1 hour Teacher/s: Elton John B. Explanation. Step 3: Work out the average of those differences. Jun 23, 2024 · Sampling Distribution: A sampling distribution is a probability distribution of a statistic obtained through a large number of samples drawn from a specific population. Proof. 4) The probability of completing in less than 43 minutes is 0. 75 compared to the population variance of 2. 0048. Note: For this standard deviation formula to be accurate, our sample size needs to be 10 % or less of the population so we can assume independence. difference between the two means Sample question: If a random sample of size 19 is drawn from a population distribution with standard deviation α = 20 then what will be the variance of the sampling distribution of the sample mean? Step 1: Figure out the population variance . Sampling distributions allow analytical considerations to be based on the sampling distribution of a statistic rather than on the joint probability distribution of all the Sampling distributions and the central limit theorem can also be used to determine the variance of the sampling distribution of the means, σ x 2, given that the variance of the population, σ 2 is known, using the following equation: where n is the size of the samples in the sampling distribution. ¯x = 8. n = number of values in the sample. The problems cover a range of sample sizes and ask for measures like the area below or above z Jan 18, 2024 · Input the population parameters in the sampling distribution calculator (μ = 161. Mar 14, 2024 · What is the Sampling Distribution Formula? A sampling distribution is defined as the probability-based distribution of specific statistics. reliable b. 3 ounces. 1 (Sampling distribution of the mean) If X1, X2, …, Xn is a random sample of size n from a population with mean μ and variance σ2, then the sample mean ˉX has a sampling distribution with mean μ and variance σ2 / n. 1 and 1. Probability P(𝐀̅) 2 1. We can use our Z table and standardize just as we are already familiar with, or can use your technology of choice. Sample Mean 𝐀̅ Frequency. n=30. Remeber, The mean is the mean of one sample and μX is the average, or center, of both X (The original distribution) and . The distribution of sample variances tends to be a normal distribution. Suppose we take samples of size 1, 5, 10, or 20 from a population that consists entirely of the numbers 0 and 1, half the population 0, half 1, so that the population mean is 0. stribution of that random variable. 1. It is also known as finite-sample distribution. Example 2. 5 = 50. No matter what the population looks like, those sample means will be roughly normally distributed given a reasonably large sample size (at least 30). In the process, users collect samples randomly but from one chosen population. 28. Calculate E (s2). It finds that when the sample size is 2, the mean of the sampling distribution is the same as the population mean, but the variance is smaller at 0. Questions asking to compute the mean, variance, and standard deviation of sampling distributions when random samples of different sizes are taken from described populations. It is most commonly measured with the following: Range: the difference between the highest and lowest values. The sample of employees had a mean 20. The importance of using a sample size minus one (n-1) for a more accurate estimate is highlighted. Jul 5, 2024 · Theorem 8. The document provides an overview and contents of a module on random sampling and sampling distributions for a Grade 11 Statistics and Probability class. LESSON PLAN FOR STATISTICS &amp; PROBABILITY I. Your result is ready. Variance: average of squared distances from the mean. To re ne the picture of a distribution about its \center of location Solution: Because the sample size of 60 is greater than 30, the distribution of the sample means also follows a normal distribution. The sampling distribution of a statistic is a probability distribution based on a large number of samples of size \ (n\) from a given population. The mean of the sample variances is the population variance. ”. 1 6. May 31, 2019 · Consider the fact though that pulling one sample from a population could produce a statistic that isn’t a good estimator of the corresponding population parameter. My object results contains 1000 sample medians for samples of size 10 drawn from that population and is a nice way to illustrate its sampling distribution. 3550. n=10. = sum of…. n = 5: Apr 23, 2022 · Table 9. I focus on the mean in this post. E (S2)<σ2E (S2)=σ2E (S2)>σ2. 92. 13. Sep 13, 2023 · I think you are getting confused about the variance of an individual and the variance of a group. Compute the sample proportion. Step 3: Click the variables you want to find the variance for and then click “Select” to move the variable names to the right window. n = sample size. = sample variance. 4 - Student's t Distribution; Lesson 27: The Central Limit Theorem. ue then the expected value equals . As shown from the example above, you can calculate the mean of every sample group chosen from the population and plot out all the data points. The proportion variance is a measure of dispersion in a proportion. An unknown distribution has a mean of 90 and a standard deviation of 15. Bootstrapping is a good practical alternative. where σx is the sample standard deviation, σ is the population standard deviation, and n is the sample size. The mean of the distribution of the sample means is μ¯. The central limit theorem says that the sampling distribution of the mean will always be normally distributed, as long as the sample size is large enough. This was a case where the expectation of a statistic y was used. Variance of the sampling distribution of the mean and the population variance. where: The formula to calculate sample variance is: s2= Σ (xi – x)2/ (n-1) where: Notice that there’s only one tiny difference between the two formulas: When we calculate population variance, we Step 1: Type your data into a column in a Minitab worksheet. Figure 6. 3 Jul 28, 2009 · This has prevented the exact characterization of the sampling distribution of the particle swarm optimizer (PSO). 2. As a random variable it has a mean, a standard deviation, and a May 1, 2024 · If the population mean is known, then the sample mean will be the same as the population mean, provided the sample size is sufficiently large. 5 0. D. Therefore, the probability that the average height of those women falls below 160 cm is about 31. B. 314039. 37% probability that the standard deviation of the weights of the sample of 200 bags of flour will fall between 1. We delve into measuring variability in quantitative data, focusing on calculating sample variance and population variance. INFORMATION. = sample mean. None of the above 3. Leads to definitions of new distributions, e. This is the main idea of the Central Sampling distribution of a sample mean. Step 2: Subtract the mean from each data point in the data set. 1 - Normal Approximation to Binomial Apr 22, 2024 · Sampling distribution in statistics represents the probability of varied outcomes when a study is conducted. Sep 19, 2023 · SS = ∑n i=1(xi − x¯¯¯)2 S S = ∑ i = 1 n ( x i − x ¯) 2. 5). The sampling distribution Steps for Calculating the Standard Deviation of the Sampling Distribution of a Sample Mean. Nov 24, 2020 · Calculate the mean and standard deviation of the sampling distribution. Sep 7, 2020 · Variability is also referred to as spread, scatter or dispersion. Step 1: Calculate the mean of the data set. 65. Expected value of product of sample moments (from a normal sample) 1. txt) or read online for free. g. (2) Similarly, the expected variance of the sample variance is given by <var(s^2)> = <var(m_2)> (3) = ((N-1)^2)/(N^3)mu_4-((N-1)(N-3 Aug 27, 2020 · It is mentioned in Stats Textbook that for a random sample, of size n from a normal distribution , with known variance, the following statistic is having a chi-square distribution with n-1 degrees of freedom: n * (sample Var)/ (Population Var) I plotted both the sample Variance & the statistic above & the distributions seem identical. 2 μ x ¯ = 8. sample mean (M11/12SP-IIId-5); and. In general, when the population is normally distributed and the population variance is \(σ^2\), all possible sample variances scaled by a constant follow the chi A. Since the mean is $\frac{1}{N}$ times the sum, the variance of the sampling distribution of the mean would be $\frac{1}{N^2}$ times the variance of the sum, which equals $\frac{σ^2}{N}$. Stack Exchange network consists of 183 Q&A communities including Stack Overflow, the largest, most trusted online community for developers to learn, share their knowledge, and build their careers. Step 1: Identify the variance of the population. Standard deviation: average distance from the mean. Viewed 6k times The sampling distribution of a statistic is a probability distribution based on a large number of samples of size n from a given population. Step 4: Click “Statistics. 2 2 3 3 3 2 4 1. Oct 17, 2017 · Distribution of the sample variance. Step 2: Click “Stat”, then click “Basic Statistics,” then click “Descriptive Statistics. 3, σ = 7. 6 years. The probability distribution for the sample variances is shown next. For finite population, the variance is defined as: σ2 = 1 N − 1 ∑(Yi −Y¯)2. 9 and the sample standard deviation = 4. Asymptotic normality of sample variance. Take a sample from a population, calculate the mean of that sample, put everything back, and do it over and over. variance of the sampling distribution of x̄ 1 - x̄ 2 d. Instead of measuring all of the fish, we randomly 26. Situation: After considering the first example on the previous part of this module, Harvey has some questions and difficulties in solving the mean and the variance of the sampling distribution of the sample means. C. First verify that the sample is sufficiently large to use the normal distribution. The following theorem will do the trick for us! Theorem. Apr 2, 2023 · The sample mean = 7. Therefore, when drawing an infinite number of random samples, the variance of the sampling distribution will be lower the Jul 13, 2024 · Let N samples be taken from a population with central moments mu_n. The formula for variance for a sample set of data is: Variance = s2 = Σ(xi The variance of a sampling distribution of a sample mean is equal to the variance of the population divided by the sample size. Math. The sample variance m_2 is then given by m_2=1/Nsum_(i=1)^N(x_i-m)^2, (1) where m=x^_ is the sample mean. 13 σ x ¯ = σ n = 1 60 = 0. 1 - The Theorem; 27. In statistics, a sampling distribution or finite-sample distribution is the probability distribution of a given random-sample-based statistic. The data follow a uniform distribution where all values between and including zero and 14 are equally likely. 1. consistent c. - Sampling distribution describes the distribution of sample statistics like means or proportions drawn from a population. Mean of the sampling distribution of the mean and the population mean; (b). σx = σ/ √n. 3. In a random sample of 30 30 recent arrivals, 19 19 were on time. 3 years and standard deviation 6. It allows making statistical inferences about the population. Variance is the sum of squares divided by the number of data points. ¯. See AnswerSee Answer done loading. Step 2: Subtract the mean and square the result. 1 years. 5. 2 - Implications in Practice; 27. The sampling distributions are: n = 1: ˉx 0 1 P(ˉx) 0. ¯x = σ √n = 1 √60 = 0. For example, Table 9. Embodo Content Standard: The learner demonstrates understanding of key concepts of sampling and sampling distributions of the sample mean. 2 . Okay, we finally tackle the probability distribution (also known as the " sampling distribution ") of the sample mean when X 1, X 2, …, X n are a random sample from a normal population with mean μ and variance σ 2. 375 3) Look up the area to the left of z = -0. Regardless of whether the population has a normal, Poisson, binomial, or any other distribution, the sampling This document provides 10 problems involving calculating statistics such as the mean, variance, and standard deviation for random samples from normally distributed populations. We want to know the average length of the fish in the tank. Form a sampling distribution of sample means. unbiased d. You may assume that the normal distribution applies. 26. It is important to keep in mind that every statistic, not just the mean, has a sampling distribution. This procedure is common in modeling data. Chapter 4. 1) Select left-tailed, in this case. The mean and variance of the sampling distribution of means can be calculated. Remy claims that the mean of the sampling distribution of the sample mean for samples of size 100 is 20. The standard deviation squared will give us the variance. Here is an example where the expectation is symbolized – we will employ this in many ways starting with lecture 4. If the variance of the sampling distribution of an estimator is smaller than all other unbiased estimators of the parameter of interest, the estimator is a. The graph will show a normal distribution, and the center will be the mean of the sampling distribution, which is the mean of the entire The sampling distributions are shown on the original scale, rather than as z scores, so you can see the effect of the shading and how much of the body falls into the range, which is marked off with thin dotted lines. For example, in this population Apr 30, 2024 · According to the central limit theorem, if X 1, X 2, …, X n is a random sample of size n taken from a population with mean µ and variance σ 2 then the sampling distribution of the sample mean tends to normal distribution with mean µ and variance σ 2 /n as sample size tends to large. 2. The variance of this sampling distribution can be computed by finding the expected value of the square of the sample variance and subtracting the square of 2. $\endgroup$ – Sep 5, 2019 · Then the ordered statistics of such random variables are well known to be beta random variables, and the median itself will be Beta ( m, m + 1) if I am not mistaken, the variance of which (check wikipedia) is. 6. population when the variance is: (a) known; (b) unknown. For instance, if the distribution is symmetric about a va. For samples of a single size n n, drawn from a population with a given mean μ μ and variance σ2 σ 2, the sampling distribution of sample means will have a mean μX¯¯¯¯¯ = μ μ X ¯ = μ and variance σ2X = σ2 n σ X 2 = σ 2 n. efficient c. b. The area is 0. To correct for this, instead of taking just one sample from the population, we’ll take lots and lots of samples, and create a sampling distribution of the sample mean. This graph shows no negative values on the horizontal axis. The population is finite and n/N ≤ . 3: All possible outcomes when two balls are sampled with replacement. What is the Oct 18, 2016 · sampling distribution for N(0,1) samples 3 Is the distribution of the ratio of the sample variance to the populaton variance from a normal population exactly or approximately Chi Square? We shall call this distribution, the sampling distribution of sample means. 33. Calculate probabilities regarding the sampling distribution. We find. Statistics and Probability. The variance of the sampling distribution of a sample proportion is 0. The proportion of all students at a particular university who also work a full time job is 0. The standard deviation of the sample means is σ¯. We can then use those assumptions to derive some basic properties of β^. The sampling distribution of the median could be calculated but is unlikely to be worth the effort. The sampling distribution of a sample mean x ¯ has: μ x ¯ = μ σ x ¯ = σ n. It should be 0. This document contains information about sampling distributions including: 1. Oct 18, 2018 · When the sample size = 1, with or without replacement does not matter. Since a sample is random, every statistic is a random variable: it varies from sample to sample in a way that cannot be predicted with certainty. 375 in the standard normal table. 4%. Types of Sampling Distribution. Statistics and Probability questions and answers. Used to get confidence intervals and to do hypothesis testing. 05. Sep 10, 2021 · The variance is a way to measure the spread of values in a dataset. The sample variance formula looks like this: Formula. According to the Central Limit Theorem, as the sample size increases, the sampling distribution of means approaches Jan 8, 2024 · The central limit theorem states: Theorem 6. pdf), Text File (. Dec 21, 2014 · When drawing a single random sample, the larger the sample is the closer the sample mean will be to the population mean (in the above quote, think of "number of trials" as "sample size", so each "trial" is an observation). Remember that the variance, {eq}\sigma^2 {/eq}, is the Specifically, you are more likely able to: 1. I begin by discussing the sampling distribution of the sample variance when sampling from The sampling distribution of the difference between means can be thought of as the distribution that would result if we repeated the following three steps over and over again: (1) sample n 1 scores from Population 1 and n 2 scores from Population 2, (2) compute the means of the two samples (M 1 and M 2 ), and (3) compute the difference between The sampling distribution of a statistic is the distribution of that statistic, considered as a random variable, when derived from a random sample of size. 50. Let n = 100 flips of a fair coin (thus p = 0. The mean can be defined as the sum of all observations divided by the total number of observations. Then. 27. If I take a sample, I don't always get the same results. Proportion Variance in Factor Analysis. 22,233. 3 - Applications in Practice; Lesson 28: Approximations for Discrete Distributions. The formula for variance for a population is: Variance = σ2 = Σ(xi − μ)2 n σ 2 = Σ ( x i − μ) 2 n. Jul 6, 2022 · The distribution of the sample means is an example of a sampling distribution. Areas between 47 and 53 for sampling distributions of n = 10 and n = 50. 2 - Sampling Distribution of Sample Mean. The expected value of m_2 for a sample size N is then given by <s^2>=<m_2>=(N-1)/Nmu_2. For a finite population, the variance is calculated using the population size and sample size. 3 - Sampling Distribution of Sample Variance. (1) To perform tasks such as hypothesis testing for a given estimated coefficient β^p, we need to pin down the sampling distribution of the OLS estimator β^ = [β1,…,βP]⊤. The expected value of the sample variance is equal to the population variance. I only recently started refreshing my knowledge of statistics, and this sentence stumps me. The reason behind this is that, for large sample sizes, the variance of the sampling distribution of the mean is low, which makes the sample mean the best point estimate for the population mean. Sampling distribution of mean. 1: Distribution of a Population and a Sample Mean. Your solution’s ready to go! Our expert help has broken down your problem into an easy-to-learn solution you can count on. 1Distribution of a Population and a Sample Mean. If the population has a normal distribution, the sampling distribution of x ¯ is a normal distribution. A sampling distribution of sample means is a probability distribution that describes the probability for each mean of all samples with the same sample size 𝐀. consider a student's exam scores have variance $\sigma^2$. Z = ∑ZiYi. 2)/8 = -0. If an arbitrarily large number of samples, each involving multiple observations (data points), were separately used in order to compute one value of a statistic (such as, for example, the sample mean or sample variance) for each sample, then the sampling Mar 27, 2023 · Figure 6. If 50 randomly selected high school students take the examination, what Jun 14, 2014 · A discussion of the sampling distribution of the sample variance. where N is population size. The first video will demonstrate the sampling distribution of the sample mean when n = 10 for the exam scores data. This not only allows sampling from complex, otherwise hard-to-sample distributions, but also changes the variance of the resulting estimator. find the mean and variance of the sampling distribution of the. Thus, (5 + 6 + 1) / 3 = 4. Use the sample variance and standard deviation calculator. be/7mYDHbrLEQo. Generate a Sampling Distribution in Excel. n \text {n} n. Draw all possible sample of size n = 3 with replacement from the population 3,6,9 and 12. Suppose we would like to generate a sampling distribution composed of 1,000 samples in which each sample size is 20 and comes from a normal distribution with a mean of 5. State the values of a and \(b\). A statistic, such as the sample mean or the sample standard deviation, is a number computed from a sample. Help Harvey in acquiring desired skills by doing Jan 31, 2022 · Sampling distributions describe the assortment of values for all manner of sample statistics. A large tank of fish from a hatchery is being delivered to the lake. \begin {equation} \chi^2\operatorname {cdf} (167. Step 1: Calculate the mean (the average weight). The word "tackle" is probably not the right choice of word, because the result Suppose X = (X1; : : : ; Xn) is a random sample from f (xj ) A Sampling distribution: the distribution of a statistic (given ) Can use the sampling distributions to compare different estimators and to determine the sample size we need. Sample variance. Examples of determining the mean, variance, and standard deviation of sampling distributions from populations with given characteristics. You should start to see some patterns. 1 with ai = 1 / n. It also involves computing z-values and probabilities for situations involving random samples and normally distributed data. Consider this example. Variance is a statistical measurement that is used to determine the spread of numbers in a data set with respect to the average value or the mean. The variance of the sampling distribution of the mean is computed as follows: \[ \sigma_M^2 = \dfrac{\sigma^2}{N}\] That is, the variance of the sampling distribution of the mean is the population variance divided by \(N\), the sample size (the number of scores used to compute a mean). Or see: how to calculate the sample variance (by hand). There can be two types of variances in statistics, namely, sample Jan 23, 2023 · Importance sampling is a clever reformulation trick, allowing us to compute expectations and other moments by sampling from a different proposal distribution. 3 9. This distribution will approach normality as n n Sep 11, 2018 · $\begingroup$ Although an analysis of the expectation of the sample variance may be sort of relevant, it does not answer the question about what happens to the sample variance itself, even when you assume--as you have implicitly done here--that the underlying distribution has a finite variance. yo qk dg ry hl ub zt be jg cc