What is the answer you got? And then, how do you tell the difference between a maximum and a minimum?Painguy said:I figured I'd take the derivative and set it equal to 0, but then what?
A minimum of normal distribution function refers to the lowest point on the curve of a normal distribution graph. It represents the smallest value that a variable can take in a normally distributed dataset.
The minimum of normal distribution function is calculated using the formula μ - 3σ, where μ is the mean and σ is the standard deviation of the dataset. This formula assumes that the dataset is normally distributed.
The minimum of normal distribution function signifies the lower limit of the expected range of values for a normally distributed variable. It is also known as the lower bound, and any values below this minimum are considered outliers.
Yes, the minimum of normal distribution function can be negative if the mean (μ) is negative and the standard deviation (σ) is relatively small. This indicates that there is a high probability of getting values that are lower than the mean in a normally distributed dataset.
The minimum of normal distribution function is used to calculate the probability of a value being within a specific range in a normally distributed dataset. It is also used to identify outliers and determine the expected range of values for a variable in a population.