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Why is less than the same thing as less than or equal to for the normal distribution computationally in statistics?
For a continuous distribution - which is what we are considering here - the probability of something being EXACTLY a specific value is zero. This is basically because there are infinite many possible values. You will only ever consider ranges of numbers, such as the probability of something being 1 and 2.
What else can I help you with?
Does mode equal median in a normal distribution?
Yes, mode equals median in a normal distribution.
What is the perfect standard normal distribution?
The standard normal distribution is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.
Is the mode and median equal in a normal distribution?
Yes.
What is true in about a normal distribution?
A normal distribution is a symmetric, bell-shaped curve characterized by its mean and standard deviation. Approximately 68% of the data falls within one standard deviation from the mean, about 95% within two standard deviations, and around 99.7% within three standard deviations, commonly referred to as the empirical rule. Additionally, the mean, median, and mode of a normal distribution are all equal and located at the center of the distribution. This property makes the normal distribution fundamental in statistics and probability theory.
If the mean of a normal distribution i s105 what is the median of the distribution?
In a normal distribution, the mean, median, and mode are all equal. Therefore, if the mean of the distribution is 105, the median of the distribution is also 105. This property holds true for any normal distribution regardless of its standard deviation.
What is computationally equivalent?
Arithmetically equal
Does mode equal median in a normal distribution?
Yes, mode equals median in a normal distribution.
What is the perfect standard normal distribution?
The standard normal distribution is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.
What is the expected value of the standard normal distribution equal to?
The expected value of the standard normal distribution is equal to the total amount of the value. It is usually equal to it when the value works out to be the same.
Is the mode and median equal in a normal distribution?
Yes.
Are the mean and median equal in a normal distribution?
Yes.
What is true in about a normal distribution?
A normal distribution is a symmetric, bell-shaped curve characterized by its mean and standard deviation. Approximately 68% of the data falls within one standard deviation from the mean, about 95% within two standard deviations, and around 99.7% within three standard deviations, commonly referred to as the empirical rule. Additionally, the mean, median, and mode of a normal distribution are all equal and located at the center of the distribution. This property makes the normal distribution fundamental in statistics and probability theory.
If the mean of a normal distribution i s105 what is the median of the distribution?
In a normal distribution, the mean, median, and mode are all equal. Therefore, if the mean of the distribution is 105, the median of the distribution is also 105. This property holds true for any normal distribution regardless of its standard deviation.
Does mode equal median in normal distribution?
Yes.
Is total area under a normal distribution finite?
Yes, and is equal to 1. This is true for normal distribution using any mean and variance.
Why is t score equal to z score in a normal distribution?
Because as the sample size increases the Student's t-distribution approaches the standard normal.
What information do you need to calculate a probability with a normal distribution?
Only the mean, because a normal distribution has a standard deviation equal to the square root of the mean.
