If you are interested in the number (rather than the proportion) of individuals in your sample with the characteristic of interest, you use the binomial distribution to find probabilities for your results. 5 - both are greater than 5. When the parameter of interest is a population proportion, p p, the underlying population distribution is composed solely of 0's and 1's thus it cannot be normally distributed. a. for(i in 1:n){. Part 2: Find the mean and standard deviation of the sampling distribution. As you can see, we added 0 by adding and subtracting the sample mean to the quantity in the numerator. Jun 30, 2020 · What the sampling distribution of p-hat is. We may sample with or without replacement. Since the standard deviation measures the spread of the distribution, and the sampling distribution is always packed tighter around the sampling mean, r x-bar < r . Find the standard deviation of the sampling distribution for the p-bar chart. Sampling distribution of a statistic is the probability That 9. Apr 23, 2022 · The concept of a sampling distribution is perhaps the most basic concept in inferential statistics. The starting values are 2 2 and 10 10. 13 σ x ¯ = σ n = 1 60 = 0. 25 0. Parameter. I n≤1/10N. Mean and Standard Deviation of the Sampling Distribution of Sample Means n x x The standard deviation of the sampling distribution of is The mean of the sampling distribution of x is x x with mean and standard deviation . #create empty vector of length n. Statistics and Probability questions and answers. The sampling distribution of x_bar is: a. Tap Calculate. As we have seen previously, it is possible but unlikely to observe a sample with 10/10 heads whereas it is much more likely to observe a sample with 5/10 heads. samples must be randomly selected from the populations. As stated in the introduction, probability theory plays an essential role as we establish results for statistical inference. The range of the sampling distribution of the means is 12 - 4 = 8. The standard deviation in both schools is 0. For example, Table 9. 8 2. If 36 samples are randomly drawn from this population then using the central limit theorem find the value that is two sample deviations above the expected value. Answer. In an SRS size of n, what is the standard deviation of the sampling distribution. The standard deviation of the sample means is σ¯. For this problem, we know p = 0. p = 7/10 (And yes I know the second example says give the sampling distribution of p-hat, but I want to know if there is a way to tell if it didn't say that. You should start to see some patterns. The sampling distribution of P¯ is. How you find a z-score for p-hat. You just need to provide the population proportion (p) (p), the sample size ( n n ), and specify the event you want to compute the probability for in the form below: Population Proportion (p) (p) =. What are the mean μX¯ μ X ¯ and standard deviation σX¯ σ X ¯ of the sample The question is asking for P (x̄ ≤ 28). Now, we can take W and do the trick of adding 0 to each term in the summation. A GPA is the grade point average of a single student. The mean and standard deviation of the tax value of all vehicles registered in a certain state are μ = $13, 525 μ = $ 13, 525 and σ = $4, 180 σ = $ 4, 180. The sample proportion p-bar provides an estimate for the population proportion p. Input: Enter the population means, standard deviation, and sample size in their respective fields. 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. 9 What is the standard deviation of the sampling distribution of p? 0. 17 and a simple random sample of 800 800 households will be selected from the population. How you find a probability for p-hat. Large. Given a sampling distribution of x -bar, made from simple random samples of size 10 , is normally distributed as N (u,0−/sqrt(n)) =N (50,6). It may be considered as the distribution of the statistic for all possible samples from the same population of a given sample size. With the larger sampling size the sampling distribution approximates a normal distribution. 5 and n ( 1 − p) = 50 ( 1 − 0. n=10. approximately normal because of the central limit theorem. For calculating the sample distribution of the sample by the sampling distribution calculator. sampling distribution of p bar (p with a bar over The sampling distribution of the sample proportion is approximately Normal with Mean μ = 0. Jan 8, 2024 · The distribution of the values of the sample proportions (p-hat) in repeated samples (of the same size) is called the sampling distribution of p-hat. not normal since n < 30. 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. Let’s return to the coin flipping example. P(X < 48) = P(Z < 48 − μ σ) = P(Z < 48 − 50 6) = P(Z < − 0. 05. A sample is large if the interval [p − 3σp^, p + 3σp^] [ p − 3 σ p ^, p + 3 σ p ^] lies wholly within the interval The Sampling Distribution of the Sample Proportion, ^p p ^. 5. When does the formula √p (1-p)/n apply to the standard deviation of phat. 25. This is the distribution of the 100 sample means you got from drawing 100 samples. The Sampling Distribution of p^ Theory says that I The average value of ^p is p and I The standard deviation of ^p is r p(1 p) n: Furthermore, if the sample size is large enough, the shape of the distribution is normal. The probability distribution of p is approximately normal with 1. 9. What test can you use to determine if the sample is large Step 1. The number of returns (presumed to be defective) were 11, 11, 13, 9, 5, 14, 10, 6, 8, and 13. The larger the sample size, the better the approximation. Here are the meanings of x bar and p hat that were used to solved the first and last question respectively: Question: The probability distribution of all possible values of the sample proportion is thea. To demonstrate this, let's simulate the sampling distribution for the sample mean of random samples from an exponential distribution with What is the difference between the normal distribution and (a) a z-distribution and (b) a sampling distribution of means? A sampling distribution is normal only if the population is normal. This unit covers how sample proportions and sample means behave in repeated samples. Sampling distribution of mean. 50. e. The mean of the distribution of the sample means is μ¯. Example 2: An unknown distribution has a mean of 80 and a standard deviation of 24. The GPAs of both schools are normally distributed. It calculates the normal distribution probability with the sample size (n), a mean values range (defined by X₁ and X₂), the population mean (μ), and the standard deviation (σ). Table 1 shows a hypothetical random sample of voters. n=30. 00:0 Figure 6. Then: Mar 26, 2023 · Verify that the sample proportion \(\hat{p}\) computed from samples of size \(900\) meets the condition that its sampling distribution be approximately normal. However, if the # of observations are large (say, >30), the sampling distribution will be tighter and more normal, compare to smaller sample, given the same # of repeatedly draws. The central limit theorem shows the following: Law of Large Numbers: As you increase sample size (or the number of samples), then the sample mean will approach the population mean. As a random variable it has a mean, a standard deviation, and a W = ∑ i = 1 n ( X i − μ σ) 2. The Sampling Distribution of 3 as long as the 10% condition is satisfied: n ≤ (1/10)N. z = ^p − p √ p×(1−p) n z = p ^ − p p × ( 1 − p) n. samples must not be dependent. Now, just to make things a little bit concrete, let's imagine that we have a population of some kind. The sum of all probabilities for all possible values must equal 1. The sample mean has mean μ¯ X = μ = 50 and standard deviation The Central Limit Theorem. Which of the following best describes the sampling distribution of the sample proportion, ^ p ? a. Same thing if this right here is m. 1. Assumptions that must be met in order to use z to test a hypothesis about a difference between two population proportions include. 40, which is the same as the population proportion p. Solution: Since the population is known to have a normal distribution. The population distribution is Normal. show? The probability distribution of p is approximately normal with a mean of 0. 17 p = . For our purposes, it will be simpler to sample with replacement. Also note how the shape of the sampling distribution changed. 43) 75 ≈ 0. all are assumptions that must be met. The sampling distribution Instructions: Use this calculator to compute probabilities associated to the sampling distribution of the sample proportion. Now that we know the mean and standard deviation of the sampling distribution of p, the final step is to determine the form or shape of the sampling distribution. (a) What is the expected value of p? Show the sampling distribution of p. If 9 9 students are randomly sampled from each school, what is the probability that: Step 1. Types of Sampling Distribution. Select and enter the probability values. When the sample size increased, the gaps between the possible sampling proportions decreased. A number that describes the population. The sampling distribution is a way to describe how a statistic behaves from sample to sample, but if we sampled the whole population, then we can calculate the parameters directly. 60, from which a sample of size n = 200 is drawn. Those who prefer Candidate are given scores of Nov 24, 2020 · To find the mean and standard deviation of this sampling distribution of sample means, we can first find the mean of each sample by typing the following formula in cell U2 of our worksheet: =AVERAGE(A2:T2) We can then hover over the bottom right corner of the cell until a tiny + appears and double click to copy this formula to every other cell Remeber, The mean is the mean of one sample and μX is the average, or center, of both X (The original distribution) and . The sampling distributions are: n= 1: x-01P(x-)0. For samples of size 30 or more, the sample mean is approximately normally distributed, with mean μX−− = μ μ X - = μ and standard deviation σX−− = σ/ n−−√ σ X - = σ / n, where n is the sample size. Consider a population with a proportion p = 0. ) Thanks and sorry again if this is a bad question. Mar 27, 2023 · The standard deviation of the sample mean \ (\bar {X}\) that we have just computed is the standard deviation of the population divided by the square root of the sample size: \ (\sqrt {10} = \sqrt {20}/\sqrt {2}\). The sampling distribution of is the distribution that would result if you repeatedly sampled voters and determined the proportion that favored Candidate . The sampling distribution of a sample proportion p ^ has: μ p ^ = p σ p ^ = p ( 1 − p) n. Apr 23, 2018 · A probability distribution function indicates the likelihood of an event or outcome. 025 What is the shape of the sampling Video transcript. 1 Sampling Distribution of a Proportion . For a simple random sample from a large population, the value of x is a binomial random variable The first video will demonstrate the sampling distribution of the sample mean when n = 10 for the exam scores data. (C) the sampling distribution of x-bar has mean μ, the Apr 23, 2022 · The mean GPA for students in School A School A is 3. It isn’t reasonable to try to create such a distribution in its entirety, but we can look at a quick example using the data file CoinTossHeads. probability density function of p bar (p with a bar over it)b. Solution: We know that mean of the sample equals the mean of the population. Given the large sample size of 100, the distribution of p bar will be approximately normal. Table 1 shows a hypothetical random sample of 10 voters. Study with Quizlet and memorize flashcards containing terms like Mu, Sampling, Statistic and more. The sampling distribution of the sample mean will have: the same mean as the population mean, \ (\mu\) Standard deviation [standard error] of \ (\dfrac {\sigma} {\sqrt {n}}\) It will be Normal (or approximately Normal) if either of these conditions is satisfied. . It explains that a sampling distribution of sample means will f Ten samples of a process measuring the number of returns per 50 receipts were taken for a local retail store. 5% chance that the mean bag weight will be less than 28g. The mean and variance of the sampling distribution are \(\mu_{\bar{X}} = 4. 4\) and \(\sigma^2_{\bar{X}} = 1. Oct 6, 2021 · The sample distribution is the distribution of income for a particular sample of eighty riders randomly drawn from the population. Feb 24, 2015 · Download files (which file shown at begin of video): https://people. The sampling distribution of the sample proportion is the probability distribution of the sample proportion. 3: All possible outcomes when two balls are sampled with replacement. Aug 10, 2019 · Fundamental concepts and simulation approach. Suppose random samples of size 100 100 are drawn from the population of vehicles. Oct 8, 2018 · This distribution of sample means is known as the sampling distribution of the mean and has the following properties: μx = μ. If a random sample of n observations is taken from a binomial population with parameter p, the sampling distribution (i. In which of the following scenarios would the distribution of the sample mean x-bar be May 24, 2021 · The probability distribution plot displays the sampling distributions for sample sizes of 25 and 100. A sampling distribution shows every possible result a statistic can take in every possible sample from a population and how often each result happens - and can help us use samples to make predictions about the chance tht something will occur. 1% chance to get a sample proportion of 50% or higher in a sample size of 75. If the sample size is large, ^p ∼ N (p, p(1−p) n) p ^ ∼ N ( p, p ( 1 − p) n). If 40 people respond “yes” then the sample proportion p = 40/100. 2. approximately normal because is always normally distributed. where p p is the population proportion and n n is the sample size. 2). In this case the normal distribution can be used to answer probability questions about sample proportions and the z z -score for the sampling distribution of the sample proportions is. It calculates the probability using the sample size (n), population proportion (p), and the specified proportions range (if you don't know the A sample of 25 observations is taken from an infinite population. The Food Marketing Institute shows that 17\% 17% of households spend more than 100 100 per week on groceries. It is important to keep in mind that every statistic, not just the mean, has a sampling distribution. Sep 12, 2021 · The Sampling Distribution of the Sample Proportion. The introductory section defines the concept and gives an example for both a discrete and a continuous distribution. Creating a Sampling Distribution. Let's say it's a bunch of balls, each of them have a number written on it. tl;dr: P-values are tail probabilities calculated from the sampling distribution of a sample-based statistic. (B) if the population distribution happens to be normal to start with, then the sampling distribution of x-bar is always normal, regardless of the sample size. 2 . Mar 26, 2016 · The larger the sample size (n) or the closer p is to 0. 50, the closer the distribution of the sample proportion is to a normal distribution. σx = σ/ √n. Formulae for mu x barand sigma x bar. A simple random sample of 144 patrons of the restaurant is taken. The sampling distributions for two different sample sizes are shown in the lower two graphs. This is true if our parent population is normal or if our sample is reasonably large ( n ≥ 30) ‍. Jul 23, 2019 · On the same assumption, find the probability that the mean of a random sample of 36 such batteries will be less than 48 months. normal if the population is normally distributed. ) And, the variance of the sample mean of the second sample is: V a r ( Y ¯ 8 = 16 2 8 = 32. 2, could be viewed as a sample from this distribution. sample_means = rep(NA, n) #fill empty vector with means. 13. (the sample mean) needs to be approximately normal. Koether (Hampden-Sydney College) Sampling Distribution of a Sample Proportion Fri, Feb 26, 2010 6 / 30 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. ¯. Sep 12, 2021 · This phenomenon of the sampling distribution of the mean taking on a bell shape even though the population distribution is not bell-shaped happens in general. (a) What is the expected value of the sampling distribution of p? 0. 2 can be viewed as a sample from this distribution right over here. By default it is a uniform distribution (all values are equally likely). Oct 23, 2020 · A sampling distribution of the mean is the distribution of the means of these different samples. 025, so there is about a 2. The probability distribution of p is approximately normal with a mean of 110. It is also a difficult concept because a sampling distribution is a theoretical distribution rather than an empirical distribution. sampling distribution of x bar (x with a bar over it)c. 43 ( 1 − 0. same as , since it considers all possible values of the sample proportion p bar (p with a bar over it)d. ¯x = 8. For example, in this population Sampling distribution of a sample mean. Jan 17, 2023 · To find the mean and standard deviation of this sampling distribution of sample means, we can first find the mean of each sample by typing the following formula in cell U2 of our worksheet: =AVERAGE(A2:T2) We can then hover over the bottom right corner of the cell until a tiny + appears and double click to copy this formula to every other cell The only thing that will be affected by the population distribution is how large the sample size n should be to get normality. Explanation: The expected value of the sampling distribution of â—ºp is equal to the population proportion p. Assume the population proportion is p = . This sampling distribution will depend on the size of the sample, the statistic being calculated and assumptions about the random If the population has N=10000, and the sample has n=10000, then there is no need to think about the sampling distribution. True False Explain. The sampling distribution of p is a special case of the sampling distribution of the mean. Mar 26, 2016 · A sampling distribution is a collection of all the means from all possible samples of the same size taken from a population. 3 shows all possible outcomes for the range of two numbers (larger number minus the smaller number). Jul 5, 2024 · From this table, the distribution of the sample mean itself can be determined (Table 8. 2 7. In the example that follows, the range of the parent population is 13 - 3 = 10. all possible samples taken from the population) will have a mean u p =p. sigmaphat=√p (1-p)/n. Note that seven of the voters prefer candidate A so the sample proportion (p) is. Statisticians use the following notation to describe probabilities: p (x) = the likelihood that random variable takes a specific value of x. 0; the mean GPA for students in School B School B is 2. Doing so, of course, doesn't change the value of W: W = ∑ i = 1 n ( ( X i − X ¯) + ( X ¯ − μ) σ) 2. 89\). The sampling distribution depends on the underlying The conditions we need for inference on a mean are: Random: A random sample or randomized experiment should be used to obtain the data. We see that the mean value for the sampling distribution does decrease and approaches the true minimum value of \$10 as the sample size gets larger. b. 2 μ x ¯ = 8. c. Show the sampling distribution of \bar {p} pˉ, the sample proportion of households spending more Study with Quizlet and memorize flashcards containing terms like The probability distribution of all possible values of the sample proportion is the _____. Solution: Because the sample size of 60 is greater than 30, the distribution of the sample means also follows a normal distribution. 5. If I take a sample, I don't always get the same results. 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 Apr 30, 2024 · Sampling distribution of a statistic is the distribution of all possible values taken by the statistic when all possible samples of a fixed size n are taken from the population. The sampling distribution is the theoretical distribution of possible values for a sample statistic. The purpose of the next video and activity is to check whether our intuition about the center, spread and shape of the sampling distribution of p-hat was correct via simulations. d. The sampling distribution is the distribution of the sample statistic \bar {x} xˉ. 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. 40. V a r ( X ¯) = σ 2 n. You're taking 12 samples, taking its mean. Here, we see that the sampling distribution for the minimum does not appear to be particularly Normal or symmetric in shape. ‍. ¯x = σ √n = 1 √60 = 0. Question A (Part 2) A sample of size 90 is selected from a population with p = 0. approximately normal because the sample size is large in comparison to the population size. seed(0) #define number of samples. Use your knowledge from Chapter 11 for finding probabilities to find the problem. 1Distribution of a Population and a Sample Mean. Another term that describes the variability of a sampling distribution. 3 days ago · This sampling distribution of the sample proportion calculator finds the probability that your sample proportion lies within a specific range: P (p₁ < p̂ < p₂), P (p₁ > p̂), or P (p₁ < p̂). How you use the Distribution of p-hat. These relationships are not coincidences, but are illustrations of the following formulas. Furthermore, the probability for a particular value Jan 18, 2024 · This normal probability calculator for sampling distributions finds the probability that your sample mean lies within a specific range. Please type the population mean ( \mu μ ), population standard deviation ( \sigma σ ), and sample size ( n n ), and provide details about the event you want to compute What does the sampling distribution of . 1. htmTopics in this video:1. Those who prefer Candidate A are given scores of 1 and those who prefer Candidate B are given scores of 0. 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. Oct 29, 2018 · The sampling distribution of sample means will approach to normal distribution, regardless of underlying population distribution, if repeatedly draw infinite N times. In this case, the population is the 10,000 test scores, each sample is 100 test scores, and each sample mean is the average of the 100 test scores. Normal: The sampling distribution of x ¯. 8. where μx is the sample mean and μ is the population mean. When the sample size n is large, the sampling distribution of phat is approximately normal. 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 . Form of the Sampling Distribution of p. 43) = 28. With the smaller sample size there were large gaps between each possible sample proportion. Since the conditions are satisfied, p ^ will have a sampling distribution that is approximately normal The sampling distribution of a sample mean x ¯ ‍ has: μ x ¯ = μ σ x ¯ = σ n ‍ 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. For a particular sample size, the variability will be largest when p = 0. Therefore, there is a 11. 3707. 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. sampling distribution of same as , since it considers all possible values of the sample proportion sampling distribution of probability density function of, A population has a mean of 180 and a standard deviation of 24. In a restaurant, the proportion of people who order coffee with their dinner is 0. highline. This will likely align with your intuition: an estimate based on a larger sample size will tend to be more accurate. Both distributions center on 100 because that is the population mean. The following code shows how to generate a sampling distribution in R: set. 33) = 0. Instructions: This Normal Probability Calculator for Sampling Distributions will compute normal distribution probabilities for sample means \bar X X ˉ, using the form below. Aug 30, 2021 · 3. The expected value of p bar, the sample proportion, is 0. Each random sample that is selected may have a different value assigned to the statistics being studied. where σx is the sample standard deviation, σ is the population standard deviation, and n is the sample size. A statistic, such as the sample mean or the sample standard deviation, is a number computed from a sample. Apr 23, 2022 · This simulation demonstrates the effect of sample size on the sampling distribution. (00:12) For a particular population proportion p, the variability in the sampling distribution decreases as the sample size n becomes larger. The mean of the sampling distribution is very close to the population mean. So P (x̄ ≤ 28) = P (z ≤ 2) = 0. samples are large enough to use a normal sampling distribution. 43, Standard deviation p ( 1 − p) n = 0. First, we should check our conditions for the sampling distribution of the sample proportion. Marginal Probability Function: Definition and Examples; Statistical Noise: Simple Definition; Bivariate Normal Distribution / Multivariate Normal (Overview) De Moivre Distribution; Von Mises Distribution: Simple Definition & Examples; Hansmann’s Distributions; Directional Distribution; Bounded Probability Distribution; Johnson’s SB Distribution 6: Sampling Distributions. Therefore, the variance of the sample mean of the first sample is: V a r ( X ¯ 4) = 16 2 4 = 64. As a sample from the sampling distribution. The distribution of x-bar is normal with a mean = 30g and standard deviation = 3/√ (9) = 1. A true sampling distribution of a sample proportion is obtained by plotting the results from all possible samples from a population of size \(n\). We will work out the sampling distribution for ^p for sample sizes of 1, 2, and 3. The sample proportion is p = x/n. However, notice how the blue distribution (N=100) clusters more tightly around the actual population mean, indicating that sample means tend to be closer to the true value. I discuss how the distribution of the sample proportion is related to the binomial distr Apr 23, 2022 · Table 9. An unknown distribution has a mean of 90 and a standard deviation of 15. Statistics from __ samples are less variable then statistics from small samples. Nov 23, 2020 · Generate a Sampling Distribution in R. Robb T. Convert each x -bar below into a z score and then find the probability using the z table (Table B). 05717 . May 10, 2014 · A discussion of the sampling distribution of the sample proportion. A sample of 64 The correct answer is a) 0. Keep reading to learn more Mean of Sampling Distribution of the Proportion. Jul 23, 2019 · Example 7. The probability distribution of p is approximately normal with a mean of 0. The second video will show the same data but with samples of n = 30. 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. Aug 10, 2019 11 min read R, Statistics, Numerical methods. n p = 50 ( 0. - [Instructor] What we're gonna do in this video is talk about the idea of a sampling distribution. For example: 100 people are asked if they are non-vegetarian. The sampling distribution of is a special case of the sampling distribution of the mean. We can use our Z table and standardize just as we are already familiar with, or can use your technology of choice. xlsx. 0 3. n= 5: Jan 8, 2024 · Likewise, we learned that the sampling distribution of the sample proportion, p-hat, is centered at the population proportion p (as long as the sample is taken at random), thus making p-hat an unbiased estimator for p. The sampling distribution of a proportion is when you repeat your survey for all possible samples of the population. 43 and n = 50. This distribution is known as the sampling distribution of the sample mean, recognition that the distribution is based on sampling data. With a large sample, the sampling distribution of a proportion will have an approximate normal Sep 13, 2022 · Sample Mean from Non-Normal Population: It turns out that even if the distribution the random samples are taken from is not normal, the sampling distribution of the sample mean is still approximately normal. p. Follow the steps below. For large samples, the sample proportion is approximately normally distributed, with mean μP^ = p μ P ^ = p and standard deviation σP^ = pq n−−√ σ P ^ = p q n. 3 9. 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. edu/mgirvin/AllClasses/210Excel2013/Ch07/Ch07. 43) = 21. approximately normal if np and n (1-P) are each at least 5. (The subscript 4 is there just to remind us that the sample mean is based on a sample of size 4. Or if m right here is 12. Depicted on the top graph is the population distribution. The sampling distribution of a statistic is the distribution of values of that statistic over all possible samples of a given size n from the population. And that sample mean, maybe it's 15. A sample of 24 observations is taken from a population that has 150 elements. The importance of the Central Limit Theorem is that it allows us to make probability statements about the sample mean, specifically in relation to its value in comparison to the This statistics video tutorial provides a basic introduction into the central limit theorem. approximately normal if np > 30 and n (1-P) > 30. There are 2 steps to solve this one. n = 10000. Find the probability that the sample proportion computed from a sample of size \(900\) will be within \(5\) percentage points of the true population proportion. kk au fu fi ug yx gi im bx yx