# data[].attributes.body
A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean.

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Z score is defined as a standard score that is used to represent the number of standard deviations by which a raw score is above or below the mean.

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The chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities.

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Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
Z score is defined as a standard score that is used to represent the number of standard deviations by which a raw score is above or below the mean.

# data[].attributes.body
the probability of the intersection of events a and B is denoted b p(a n b). if events a and b are mutually exclusive , p(a n b) = 0.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
The chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
Standard deviation is the average deviation of the whole sample from the mean.

# data[].attributes.body
a measure of how dispersed the data is in relation to the mean.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.headline
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.subject
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

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Statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance.

# data[].attributes.body
a measure of how dispersed the data is in relation to the mean.

# data[].attributes.body
Z score is defined as a standard score that is used to represent the number of standard deviations by which a raw score is above or below the mean.

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it's a measure of how many standard deviations below or above the population mean a raw score is. A z-score can be placed on a normal distribution curve.

# data[].attributes.subject
it's a measure of how many standard deviations below or above the population mean a raw score is. A z-score can be placed on a normal distribution curve.

# data[].attributes.body
it's a measure of how many standard deviations below or above the population mean a raw score is. A z-score can be placed on a normal distribution curve.

# data[].attributes.body
a z - score is a numerical measurement that describes a values relationships to the mean of a group of values.

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A standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. Hector B

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is a measure of how dispersed the data is in relation to the mean

# data[].attributes.body
a measure of how dispersed the data is in relation to the mean.

# data[].attributes.body
the probability of the intersection of events a and B is denoted b p(a n b). if events a and b are mutually exclusive , p(a n b) = 0.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

# data[].attributes.body
A measure of how spread out numbers are

# data[].attributes.body
A standard deviation (or σ) is a measure of how dispersed the data is in relation to the mean. Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

# data[].attributes.body
Low standard deviation means data are clustered around the mean, and high standard deviation indicates data are more spread out.

# data[].attributes.body
Standard deviation is a statistical measure of variability that indicates the average amount that a set of numbers deviates from their mean.

# data[].attributes.body
Standard deviation is a measure of the amount of variation or dispersion of a set of values.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values

# data[].attributes.body
A Z-score gives you an idea of how far from the mean a data point is.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values.

# data[].attributes.body
The probability of the intersection of two events A and B is P (A) x P (B) when A and B are independent.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values.

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A z-score describes the position of a raw score in terms of its distance from the mean, when measured in standard deviation units.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. Z-score is measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score.

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A Z-score gives you an idea of how far from the mean a data point is. Hector B

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values.

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The standard score (more commonly referred to as a z-score) is a very useful statistic because it (a) allows us to calculate the probability of a score occurring within our normal distribution and (b) enables us to compare two scores that are from different normal distributions.

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a numerical measurement that describes a value's relationship to the mean of a group of values.

# data[].attributes.body
a numerical measurement that describes a value's relationship to the mean of a group of values.

# data[].attributes.body
A Z-score is a numerical measurement that describes a value's relationship to the mean of a group of values.

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The probability of the intersection of two events A and B is P ( A) ∗ P ( B) when A and B are independent.

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The probability of the intersection of two events A and B is P ( A) ∗ P ( B) when A and B are independent.

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The probability of the intersection of Events A and B is denoted by P(A ∩ B). If Events A and B are mutually exclusive, P(A ∩ B) = 0.

# data[].attributes.body
the probability of the intersection of Events A and B is denoted by P(A ∩ B). If Events A and B are mutually exclusive, P(A ∩ B) = 0.

# data[].attributes.body
the probability of the intersection of Events A and B is denoted by P(A ∩ B). If Events A and B are mutually exclusive, P(A ∩ B) = 0.

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By the product of probabilities for example
1/2*1/2=1/4

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The probability of the intersection of two or more events is the product of the probabilities

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You would define the probability of the intersection of two events by multiplying the probability of the first event by the second. Hector Bonilla

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The probability of the intersection of two events would be defined as the product of the probabilities.

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the probability of the intersection of Events A and B is denoted by P(A ∩ B)The chance of all of two or more events occurring is called the intersection of events anyla 

# data[].attributes.subject
the probability of the intersection of Events A and B is denoted by P(A ∩ B)The chance of all of two or more events occurring is called the intersection of events anyla 

# data[].attributes.body
the probability of the intersection of Events A and B is denoted by P(A ∩ B). If Events A and B are mutually exclusive, P(A ∩ B) = 0.

# data[].attributes.body
The chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities.

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The  product of the probabilities .

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I would define the probability of the intersection of two events as the likelihood that two separate events cross over due to either a similarity or just occurring at the same place at the same time.

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The chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities. In the case of two coin flips, for example, the probability of observing two heads is 1/2*1/2 = 1/4.

# data[].attributes.body
The chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities. In the case of two coin flips, for example, the probability of observing two heads is 1/2*1/2 = 1/4.

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çThe chance of all of two or more events occurring is called the intersection of events. For independent events, the probability of the intersection of two or more events is the product of the probabilities

# data[].attributes.body
For independent events, the probability of the intersection of two or more events is the product of the probabilities. In the case of two coin flips, for example, the probability of observing two heads is 1/2*1/2 = 1/4.

# data[].attributes.body
By the product of the probabilities for example

1/2*1/2 = 1/4

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the product of the probabilities.