nop its not
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.
Yes, that's true. In a normal distribution, a smaller standard deviation indicates that the data points are closer to the mean, resulting in a taller and narrower curve. Conversely, a larger standard deviation leads to a wider and shorter curve, reflecting more variability in the data. Thus, the standard deviation directly affects the shape of the normal distribution graph.
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.
Smaller
The standard normal curve is symmetrical.
Mean = 0 Standard Deviation = 1
Yes. By definition. A normal distribution has a bell-shaped density curve described by its mean and standard deviation. The density curve is symmetrical(i.e., an exact reflection of form on opposite sides of a dividing line), and centered about (divided by) its mean, with its spread (width) determined by its standard deviation. Additionally, the mean, median, and mode of the distribution are equal and located at the peak (i.e., height of the curve).
1
The distance between the middle and the inflection point is the standard deviation.
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.
It is 15 points.
No, they are rarely the same.
The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.
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.
Smaller
The mean must be 0 and the standard deviation must be 1. Use the formula: z = (x - mu)/sigma