The mean of a standard normal curve is 0. This curve, which is a type of probability distribution known as the standard normal distribution, is symmetric and bell-shaped, centered around the mean. Additionally, the standard deviation of a standard normal curve is 1, which helps define the spread of the data around the mean.
A standard normal distribution has a mean of zero and a standard deviation of 1. A normal distribution can have any real number as a mean and the standard deviation must be greater than zero.
No, they are rarely the same.
To find the area under the standard normal curve between -1.33 and the mean (0), we can use the standard normal distribution table or a calculator. The area to the left of -1.33 is approximately 0.0918. Since the total area under the curve is 1 and the curve is symmetrical around the mean, the area between -1.33 and 0 is about 0.5 - 0.0918 = 0.4082. Thus, the area under the curve from -1.33 to the mean is approximately 0.4082.
No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.
Mean and Standard Deviation
It is a normal curve with mean = 0 and variance = 1.
Mean = 0 Standard Deviation = 1
A standard normal distribution has a mean of zero and a standard deviation of 1. A normal distribution can have any real number as a mean and the standard deviation must be greater than zero.
The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.
The standard normal curve is symmetrical.
No, they are rarely the same.
the standard normal curve 2
The area under the standard normal curve is 1.
The mean must be 0 and the standard deviation must be 1. Use the formula: z = (x - mu)/sigma
No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.
Mean and Standard Deviation
Because the standard deviation is one of the two parameters (the other being the mean) which define the Normal curve. The mean defines the location and the standard deviation defines its shape.