*RPubs Sampling Distribution in R The Sampling Distribution of the Sample Mean. If repeated random samples of a given size n are taken from a population of values for a quantitative variable, where the population mean is μ (mu) and the population standard deviation is σ (sigma) then the mean of …*

Deп¬Ѓne the sampling distribution of the mean. Study Term. Note that the spread of the sampling distribution of the mean decreases as the sample size increases. An example of the effect of sample size is shown above. Notice that the mean of the distribution is not affected by sample size. Click here for an interactive demonstration of sampling distributions., What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution..

We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean. Distribution of the Sample Mean; The distribution of the sample mean is a probability distribution for all possible values of a sample mean, computed from a sample of size n. For example: A statistics class has six students, ages displayed below. Construct a sampling distribution of the mean of age for samples (n = 2). The standard

Which population parameter does the sampling distribution of sample proportions center around? Median Mean Range P (rho) Which of the following is true with regard to the degree of freedom? Sum of all the differences between the data value and the sample mean can be any number Its value is always one less than the sample size Its value is always one more than the sample size Its value is the The Sampling Distribution of the Sample Mean. If repeated random samples of a given size n are taken from a population of values for a quantitative variable, where the population mean is μ (mu) and the population standard deviation is σ (sigma) then the mean of …

That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for … SAMPLING DISTRIBUTIONS • A sampling distribution acts as a frame of reference for statistical decision making. • It is a theoretical probability distribution of the possible values of some sample statistic that would occur if we were to draw all

SAMPLING DISTRIBUTIONS • A sampling distribution acts as a frame of reference for statistical decision making. • It is a theoretical probability distribution of the possible values of some sample statistic that would occur if we were to draw all Each sample has its own average value, and the distribution of these averages is called the “sampling distribution of the sample mean. ” This distribution is normal since the underlying population is normal, although sampling distributions may also often be close to …

As the sample size increases, the mean of the sampling distribution of the mean will approach the population mean of μ, and the variance will approach σ 2 /N, where N is the sample size. You can think of a sampling distribution as a relative frequency distribution with a large number of samples. 9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean.

9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean. Nov 22, 2011 · sampling distribution of sample mean from normal data. Mail Print Twitter Facebook. This is an investigation of what happens to the sample mean when you take samples from a (normally distributed) population. First (this is the easiest way) we need a population to sample from. Select Data, Simulate Data and Normal, then fill out the dialog box

The Sampling Distribution of the Mean. The sampling distribution of the mean is a distribution of sample means. This distribution may be described with the parameters and These parameters are closely related to the parameters of the population distribution, with the … For an example, we will consider the sampling distribution for the mean. The mean of a population is a parameter that is typically unknown. If we select a sample of size 100, then the mean of this sample is easily computed by adding all values together and then dividing by …

For an example, we will consider the sampling distribution for the mean. The mean of a population is a parameter that is typically unknown. If we select a sample of size 100, then the mean of this sample is easily computed by adding all values together and then dividing by … In the Appendix to Chapter 4, we showed how to compute probabilities for the mean of a normal distribution. Here we show similar calculations for the distribution of the sampling variance for normal data. Consider again the pine seedlings, where we had a sample of 18 having a population mean of 30 cm and a population variance of 90 cm2. What is the

In this section we review sampling distributions, especially properties of the mean and standard deviation of a sample, viewed as random variables. We look at hypothesis testing of these parameters, as well as the related topics of confidence intervals, effect size and statistical power. The Sampling Distribution of the Sample Mean. If repeated random samples of a given size n are taken from a population of values for a quantitative variable, where the population mean is μ (mu) and the population standard deviation is σ (sigma) then the mean of …

Which population parameter does the sampling distribution of sample proportions center around? Median Mean Range P (rho) Which of the following is true with regard to the degree of freedom? Sum of all the differences between the data value and the sample mean can be any number Its value is always one less than the sample size Its value is always one more than the sample size Its value is the What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution.

PLEASE ANSWER I DON"T KNOW WHAT I"M DOING!!! Wyzant. We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean., Nov 22, 2011 · sampling distribution of sample mean from normal data. Mail Print Twitter Facebook. This is an investigation of what happens to the sample mean when you take samples from a (normally distributed) population. First (this is the easiest way) we need a population to sample from. Select Data, Simulate Data and Normal, then fill out the dialog box.

PLEASE ANSWER I DON"T KNOW WHAT I"M DOING!!! Wyzant. Start studying Ch 7 - The Sampling Distribution of the Sample Mean. Learn vocabulary, terms, and more with flashcards, games, and other study tools., notes, the distribution of sample means is normally distributed. 11 X This is the histogram that results from 100 different samples, each with 32 students. This histograms essentially shows a sampling distribution of sample means. The mean is very close to µ=3.88 The Distribution of Sample Means ! The distribution of sample means is the.

Unit 5 Sampling Distributions of Statistics. Question: The Assets (in Billions Of Dollars) Of The Four Wealthiest People In A Particular Country Are 39, 33, 16, 15. Assume That Samples Of Size N = 2 Are Randomly Selected With Replacement From This Population Of Four Values. After Identifying The 16 Different Possible Samples And Finding The Mean Of Each Sample, Construct A Table Representing The Sampling https://en.wikipedia.org/wiki/Central_limit_theorem What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution..

Complete a-e for the population data: 5,7,9 A. Find the mean u of the variable. B. For each of the possible sample sizes, construct a table w/ all possible samples and their sample means, and draw a dotplot for the sampling distribution of the sample mean. The sampling distribution of the sample mean is a probability distribution of all the sample means. Let’s say you had 1,000 people, and you sampled 5 people at a time and calculated their average height. If you kept on taking samples (i.e. you repeated the sampling a thousand times),

That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for … PLEASE ANSWER I DON"T KNOW WHAT I"M DOING!!! After identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean. In the table, values of the sample mean that are the same have been combined.

In this section we review sampling distributions, especially properties of the mean and standard deviation of a sample, viewed as random variables. We look at hypothesis testing of these parameters, as well as the related topics of confidence intervals, effect size and statistical power. That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for …

Repeated sampling with replacement for different sample sizes is shown to produce different sampling distributions. A sampling distribution therefore depends very much on sample size. As an example, with samples of size two, we would first draw a number, say a 6 (the chance of this is 1 in 5 = 0.2 or 20%. PLEASE ANSWER I DON"T KNOW WHAT I"M DOING!!! After identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean. In the table, values of the sample mean that are the same have been combined.

Nov 12, 2014 · Big Idea Each student will obtain and calculate the mean for eight different simple random samples of size 4 from a population of exam grades. The class will construct a histogram of sample means to illustrate a sampling distribution. The teacher will demonstrate a sampling distribution from the same population using sample size n=2. Students... For an example, we will consider the sampling distribution for the mean. The mean of a population is a parameter that is typically unknown. If we select a sample of size 100, then the mean of this sample is easily computed by adding all values together and then dividing by …

In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution. Start studying Ch 7 - The Sampling Distribution of the Sample Mean. Learn vocabulary, terms, and more with flashcards, games, and other study tools.

We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean. In turn, they will report their mean to the instructor, who will record these. The instructor can then create a histogram based on their sample means and explain that they have created a sampling distribution. Afterwards, the applet can be used to demonstrate properties of the sampling distribution.

In the Appendix to Chapter 4, we showed how to compute probabilities for the mean of a normal distribution. Here we show similar calculations for the distribution of the sampling variance for normal data. Consider again the pine seedlings, where we had a sample of 18 having a population mean of 30 cm and a population variance of 90 cm2. What is the PLEASE ANSWER I DON"T KNOW WHAT I"M DOING!!! After identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean. In the table, values of the sample mean that are the same have been combined.

Jun 10, 2014 · 7-21 7.2 The Sampling Distribution of the Sample Mean Example: Draw a sampling distribution of the sample mean from a population of X={1,2,3,4,5,6} from a sample of n=3 without replacement. Process: List all possible samples Calculate each mean of all possible samples Construct the distribution of the sample means LO 7.5 22. Sampling Distribution of the Sample Mean. a. After identifying the 16 different possible samples, find the mean of each sample, then construct a table representing the sampling distribution of the sample mean. In the table, combine values of the sample mean that are the same. (Hint: See Table 6-4 in Example 1.) b.

What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution. We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean.

Jun 10, 2014 · 7-21 7.2 The Sampling Distribution of the Sample Mean Example: Draw a sampling distribution of the sample mean from a population of X={1,2,3,4,5,6} from a sample of n=3 without replacement. Process: List all possible samples Calculate each mean of all possible samples Construct the distribution of the sample means LO 7.5 22. Jun 26, 2014 · The assets (in billions of dollars) of the four wealthiest people in a particular country are 29,27,20,12. Assume the samples of size n=2 are randomly selected with replacement from this population of four values. After Identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean.

Unit 5 Sampling Distributions of Statistics. 9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean., In this section we review sampling distributions, especially properties of the mean and standard deviation of a sample, viewed as random variables. We look at hypothesis testing of these parameters, as well as the related topics of confidence intervals, effect size and statistical power..

Sampling Distributions Real Statistics Using Excel. Jun 26, 2014 · The assets (in billions of dollars) of the four wealthiest people in a particular country are 29,27,20,12. Assume the samples of size n=2 are randomly selected with replacement from this population of four values. After Identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean., Statistical Tests. Use information from the sample to determine whether a certain statement about the parameter of interest is true. Statistical tests are also referred to as hypothesis tests.. For instance, suppose a news station claims that the President’s current approval rating is more than 75%..

Question: The Assets (in Billions Of Dollars) Of The Four Wealthiest People In A Particular Country Are 39, 33, 16, 15. Assume That Samples Of Size N = 2 Are Randomly Selected With Replacement From This Population Of Four Values. After Identifying The 16 Different Possible Samples And Finding The Mean Of Each Sample, Construct A Table Representing The Sampling Jan 16, 2014 · Sampling Distribution of the Sample Mean. Inferential testing uses the sample mean (x̄) to estimate the population mean (μ).Typically, we use the data from a single sample, but there are many possible samples of the same size that could be drawn from that population.

This is usually the case. If we have sample data, then we can use bootstrapping methods to construct a bootstrap sampling distribution to construct a confidence interval. Bootstrapping is a resampling procedure that uses data from one sample to generate a sampling distribution by repeatedly taking random samples from the known sample. Statistical Tests. Use information from the sample to determine whether a certain statement about the parameter of interest is true. Statistical tests are also referred to as hypothesis tests.. For instance, suppose a news station claims that the President’s current approval rating is more than 75%.

Each sample has its own average value, and the distribution of these averages is called the “sampling distribution of the sample mean. ” This distribution is normal since the underlying population is normal, although sampling distributions may also often be close to … 9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean.

Distribution of the Sample Mean; The distribution of the sample mean is a probability distribution for all possible values of a sample mean, computed from a sample of size n. For example: A statistics class has six students, ages displayed below. Construct a sampling distribution of the mean of age for samples (n = 2). The standard Question: The Assets (in Billions Of Dollars) Of The Four Wealthiest People In A Particular Country Are 39, 33, 16, 15. Assume That Samples Of Size N = 2 Are Randomly Selected With Replacement From This Population Of Four Values. After Identifying The 16 Different Possible Samples And Finding The Mean Of Each Sample, Construct A Table Representing The Sampling

Jun 26, 2014 · The assets (in billions of dollars) of the four wealthiest people in a particular country are 29,27,20,12. Assume the samples of size n=2 are randomly selected with replacement from this population of four values. After Identifying the 16 different possible samples and finding the mean of each sample, construct a table representing the sampling distribution of the sample mean. Jan 16, 2014 · Sampling Distribution of the Sample Mean. Inferential testing uses the sample mean (x̄) to estimate the population mean (μ).Typically, we use the data from a single sample, but there are many possible samples of the same size that could be drawn from that population.

Each sample has its own average value, and the distribution of these averages is called the “sampling distribution of the sample mean. ” This distribution is normal since the underlying population is normal, although sampling distributions may also often be close to … Jan 16, 2014 · Sampling Distribution of the Sample Mean. Inferential testing uses the sample mean (x̄) to estimate the population mean (μ).Typically, we use the data from a single sample, but there are many possible samples of the same size that could be drawn from that population.

– Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample variance • Draw 10,000 random samples of size N=5 from a uniform distribution on [0,32]. This is usually the case. If we have sample data, then we can use bootstrapping methods to construct a bootstrap sampling distribution to construct a confidence interval. Bootstrapping is a resampling procedure that uses data from one sample to generate a sampling distribution by repeatedly taking random samples from the known sample.

What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution. Jul 24, 2009 · Topics for: 1.Learn how to construct a Sampling Distribution Of Sample Mean 2.See that Population Mean = Mean of all Sample Means 3.See how to calculate the

For an example, we will consider the sampling distribution for the mean. The mean of a population is a parameter that is typically unknown. If we select a sample of size 100, then the mean of this sample is easily computed by adding all values together and then dividing by … Complete a-e for the population data: 5,7,9 A. Find the mean u of the variable. B. For each of the possible sample sizes, construct a table w/ all possible samples and their sample means, and draw a dotplot for the sampling distribution of the sample mean.

Jul 26, 2019 · 9.7 Deﬁne the sampling distribution of the mean. 9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. SAMPLING DISTRIBUTIONS • A sampling distribution acts as a frame of reference for statistical decision making. • It is a theoretical probability distribution of the possible values of some sample statistic that would occur if we were to draw all

Excel Statistics 76 Sampling Distribution Of Sample Mean. Statistical Tests. Use information from the sample to determine whether a certain statement about the parameter of interest is true. Statistical tests are also referred to as hypothesis tests.. For instance, suppose a news station claims that the President’s current approval rating is more than 75%., In the Appendix to Chapter 4, we showed how to compute probabilities for the mean of a normal distribution. Here we show similar calculations for the distribution of the sampling variance for normal data. Consider again the pine seedlings, where we had a sample of 18 having a population mean of 30 cm and a population variance of 90 cm2. What is the.

Excel Statistics 76 Sampling Distribution Of Sample Mean. In the Appendix to Chapter 4, we showed how to compute probabilities for the mean of a normal distribution. Here we show similar calculations for the distribution of the sampling variance for normal data. Consider again the pine seedlings, where we had a sample of 18 having a population mean of 30 cm and a population variance of 90 cm2. What is the, The Sampling Distribution of the Mean. The sampling distribution of the mean is a distribution of sample means. This distribution may be described with the parameters and These parameters are closely related to the parameters of the population distribution, with the ….

Solved The Assets (in Billions Of Dollars) Of The Four We. That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for …, This is usually the case. If we have sample data, then we can use bootstrapping methods to construct a bootstrap sampling distribution to construct a confidence interval. Bootstrapping is a resampling procedure that uses data from one sample to generate a sampling distribution by repeatedly taking random samples from the known sample..

statistics 1? Yahoo Answers. That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for … https://en.wikipedia.org/wiki/Central_limit_theorem The sampling distribution of the sample mean is a probability distribution of all the sample means. Let’s say you had 1,000 people, and you sampled 5 people at a time and calculated their average height. If you kept on taking samples (i.e. you repeated the sampling a thousand times),.

9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean. Complete a-e for the population data: 5,7,9 A. Find the mean u of the variable. B. For each of the possible sample sizes, construct a table w/ all possible samples and their sample means, and draw a dotplot for the sampling distribution of the sample mean.

That distribution of sample statistics is known as the sampling distribution. If the sample size is large, the sampling distribution will be approximately normally with a mean equal to the population parameter. The following pages include examples of using StatKey to construct sampling distributions for … What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution.

We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean. Jan 16, 2014 · Sampling Distribution of the Sample Mean. Inferential testing uses the sample mean (x̄) to estimate the population mean (μ).Typically, we use the data from a single sample, but there are many possible samples of the same size that could be drawn from that population.

We select all the samples of 4 such social workers from the population of 6 to create a sampling distribution of the means. 1) find the mean and standard deviation of this population 2) List the 15 samples size 4 and their means from this population 3) List the sample mean, frequency and probability for each sample mean. 9.8 Specify three important properties of the sampling distribution of the mean. 9.9 If we took a random sample of 35 subjects from some population, the associated sampling distribution of the mean would have the following properties (true or false). (a) Shape would approximate a normal curve. (b) Mean would equal the one sample mean.

Which population parameter does the sampling distribution of sample proportions center around? Median Mean Range P (rho) Which of the following is true with regard to the degree of freedom? Sum of all the differences between the data value and the sample mean can be any number Its value is always one less than the sample size Its value is always one more than the sample size Its value is the Jan 16, 2014 · Sampling Distribution of the Sample Mean. Inferential testing uses the sample mean (x̄) to estimate the population mean (μ).Typically, we use the data from a single sample, but there are many possible samples of the same size that could be drawn from that population.

What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution. The sampling distribution of the sample mean is a probability distribution of all the sample means. Let’s say you had 1,000 people, and you sampled 5 people at a time and calculated their average height. If you kept on taking samples (i.e. you repeated the sampling a thousand times),

Which population parameter does the sampling distribution of sample proportions center around? Median Mean Range P (rho) Which of the following is true with regard to the degree of freedom? Sum of all the differences between the data value and the sample mean can be any number Its value is always one less than the sample size Its value is always one more than the sample size Its value is the What will you do if you cannot use the t-interval? What do we do when the above conditions are not satisfied? If you do not know if the distribution comes from a normally distributed population and the sample size is small (i.e \(n<30\)), you can use the Normal Probability Plot to check if the data come from a normal distribution.

– Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample variance • Draw 10,000 random samples of size N=5 from a uniform distribution on [0,32]. The sampling distribution of the sample mean is a probability distribution of all the sample means. Let’s say you had 1,000 people, and you sampled 5 people at a time and calculated their average height. If you kept on taking samples (i.e. you repeated the sampling a thousand times),

Nov 22, 2011 · sampling distribution of sample mean from normal data. Mail Print Twitter Facebook. This is an investigation of what happens to the sample mean when you take samples from a (normally distributed) population. First (this is the easiest way) we need a population to sample from. Select Data, Simulate Data and Normal, then fill out the dialog box Which population parameter does the sampling distribution of sample proportions center around? Median Mean Range P (rho) Which of the following is true with regard to the degree of freedom? Sum of all the differences between the data value and the sample mean can be any number Its value is always one less than the sample size Its value is always one more than the sample size Its value is the

Each sample has its own average value, and the distribution of these averages is called the “sampling distribution of the sample mean. ” This distribution is normal since the underlying population is normal, although sampling distributions may also often be close to … What we are seeing in these examples does not depend on the particular population distributions involved. In general, one may start with any distribution and the sampling distribution of the sample mean will increasingly resemble the bell-shaped normal curve as the sample size increases. This is the content of the Central Limit Theorem.

– Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample mean. – Construct the histogram of the sampling distribution of the sample variance • Draw 10,000 random samples of size N=5 from a uniform distribution on [0,32]. What we are seeing in these examples does not depend on the particular population distributions involved. In general, one may start with any distribution and the sampling distribution of the sample mean will increasingly resemble the bell-shaped normal curve as the sample size increases. This is the content of the Central Limit Theorem.

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