What is the 'Central Limit Theorem  CLT'
The central limit theorem (CLT) is a statistical theory that states that given a sufficiently large sample size from a population with a finite level of variance, the mean of all samples from the same population will be approximately equal to the mean of the population. Furthermore, all of the samples will follow an approximate normal distribution pattern, with all variances being approximately equal to the variance of the population divided by each sample's size.
BREAKING DOWN 'Central Limit Theorem  CLT'
This statistical theory is very useful when examining returns for a given stock or index because it simplifies many analysis procedures. An appropriate sample size depends on the data available, but generally speaking, having a sample size of at least 50 observations is sufficient. Due to the relative ease of generating financial data, it is often easy to produce much larger sample sizes.

Sampling
A process used in statistical analysis in which a predetermined ... 
Sampling Error
A statistical error to which an analyst exposes a model simply ... 
Sampling Distribution
A probability distribution of a statistic obtained through a ... 
Sample
A subset containing the characteristics of a larger population. ... 
Systematic Sampling
A type of probability sampling method in which sample members ... 
Representative Sample
A subset of a statistical population that accurately reflects ...

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Explaining the Central Limit Theorem
Central limit theorem is a fundamental concept in probability theory. 
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How Does Sampling Work?
Sampling is a term used in statistics that describes methods of selecting a predefined representative number of data from a larger data population. 
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What is Systematic Sampling?
Systematic sampling is similar to random sampling, but it uses a pattern for the selection of the sample. 
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Explaining Standard Error
Standard error is a statistical term that measures the accuracy with which a sample represents a population. 
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What is a Representative Sample?
In statistics, a representative sample accurately represents the makeup of various subgroups in an entire data pool. 
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Understanding the Simple Random Sample
A simple random sample is a subset of a statistical population in which each member of the subset has an equal probability of being chosen. 
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How to Use Stratified Random Sampling
Stratified random sampling is a technique best used with a sample population easily broken into distinct subgroups. Samples are then taken from each subgroup based on the ratio of the subgroupâ€™s ... 
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Explaining Variance
Variance is a measurement of the spread between numbers in a data set. 
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Birch Box Review: Is It Worth It?
Learn more about the convenience of the subscription beauty box industry, and discover why the Birchbox company in particular has become so popular. 
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Understanding Statistics
Statistics provide the means to analyze data and then summarize it into a numerical form.

How can a representative sample lead to sampling bias?
Learn how using representative samples alone is not enough to make sampling bias negligible and why elements such as randomization ... Read Answer >> 
What is the difference between systematic sampling and cluster sampling?
Learn about the differences between systematic sampling and cluster sampling, including how the samples are created for each ... Read Answer >> 
What's the difference between a representative sample and a convenience sample?
Learn the difference between convenience sampling and representative sampling and the advantages and disadvantages of each ... Read Answer >> 
What percentage of the population do you need in a representative sample?
Learn about representative samples and how they are used in conjunction with other strategies to create useful data with ... Read Answer >> 
How do researchers ensure that a simple random sample is an accurate representation ...
Learn which methods researchers employ to ensure that a simple random sample best approximates the larger population being ... Read Answer >> 
What's the difference between a representative sample and a random sample?
Explore the differences between representative samples and random samples, and discover how they are often used in tandem ... Read Answer >>