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.
The Normal distribution is continuous. As a result the probability of getting exactly a single value, X = x, is zero. If possible, this would be represented by the "area" below the point x on the Normal curve. Since there is no width to this area, its value is zero.
It follows then, Pr(X < =x) - Pr(X < x) = Pr(X = x) = 0,
or equivalently, Pr(X < =x) = Pr(X < x)
Yes, mode equals median in a 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.
Yes.
Yes.
Yes, and is equal to 1. This is true for normal distribution using any mean and variance.
Arithmetically equal
Yes, mode equals median in a 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.
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.
Yes.
Yes.
Yes.
Yes, and is equal to 1. This is true for normal distribution using any mean and variance.
Because as the sample size increases the Student's t-distribution approaches the standard normal.
Only the mean, because a normal distribution has a standard deviation equal to the square root of the mean.
The answer will depend on the underlying distribution for the variable. You may not simply assume that the distribution is normal.
True. You can find many references including wikipedia on the Normal distribution on the internet.