The Gaussian "Bell" Curve has probability density function: f(x)= exp{-((x-mu)2/(2*sigma2)) } / (sigma*sqrt(2*pi)) where mu=mean & sigma=standard deviation
probability density distribution
Probability Density Function
The probability density function of a random variable can be either chosen from a group of widely used probability density functions (e.g.: normal, uniform, exponential), based on theoretical arguments, or estimated from the data (if you are observing data generated by a specific density function). More material on density functions can be found by following the links below.
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)
yes, h=1/sigma(standard deviation)
The Gaussian "Bell" Curve has probability density function: f(x)= exp{-((x-mu)2/(2*sigma2)) } / (sigma*sqrt(2*pi)) where mu=mean & sigma=standard deviation
No. f is a letter of the Roman alphabet. It cannot be a probability density function.
The question gives summary statistics for a population. If the underlying distribution is Gaussian, or some other known distribution, then the probability density function can be calculated. Even so, there is no question and so nothing to "solve".
A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.
probability density distribution
Probability Density Function
If you have a variable X distributed with mean m and standard deviation s, then the z-score is (x - m)/s. If X is normally distributed, or is the mean of a random sample then Z has a Standard Normal distribution: that is, a Gaussian distribution with mean 0 and variance 1. The probability density function of Z is tabulated so that you can check the probability of observing a value as much or more extreme.
The probability density function of a random variable can be either chosen from a group of widely used probability density functions (e.g.: normal, uniform, exponential), based on theoretical arguments, or estimated from the data (if you are observing data generated by a specific density function). More material on density functions can be found by following the links below.
what is density curve
A probability density function.
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)