What do you understand by the term normal distribution?
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The normal distribution, also known as the Gaussian or standard normal distribution, is the probability distribution that plots all of its values in a symmetrical fashion, and most of the results are situated around the probability's mean. Values are equally likely to plot either above or below the mean.
The normal distribution is a probability distribution that (roughly) describes many common datasets in the real world. It is the most common type of distribution, and it arises naturally in statistics through random sampling techniques.
Nowadays, it is more common to show up as a model for the "lifespan" of a product, like a lightbulb, or the outcome of standardized tests, like IQ. Biological measurements, like height or weight, are often estimated with normal distributions .
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The normal distribution is a probability distribution that (roughly) describes many common datasets in the real world. It is the most common type of distribution, and it arises naturally in statistics through random sampling techniques.
Nowadays, it is more common to show up as a model for the "lifespan" of a product, like a lightbulb, or the outcome of standardized tests, like IQ. Biological measurements, like height or weight, are often estimated with normal distributions .
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Normal Distribution
Common Continuous Probability Distribution is stated for Normal Distribution in statistics for advanced data evaluation and interpretation
Data utility - Random variable ∈ R
classification -
Normal Distribution -
1.) Probability Distribution Function [ P.D.F. ]
2.) Cumulative Distribution Function [ C.D.F. ]
STANDARD CASE -
STANDARD NORMAL DISTRIBUTION FUNCTION
WITH σ = 1 and μ = 0
Stated as PDF
INFLECTION POINTS - ±1
Common Continuous Probability Distribution is stated for Normal Distribution in statistics for advanced data evaluation and interpretation
Data utility - Random variable ∈ R
classification -
Normal Distribution -
1.) Probability Distribution Function [ P.D.F. ]
2.) Cumulative Distribution Function [ C.D.F. ]
STANDARD CASE -
STANDARD NORMAL DISTRIBUTION FUNCTION
WITH σ = 1 and μ = 0
Stated as PDF
INFLECTION POINTS - ±1
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