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.
probability density distribution
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)
See related link, In quantum mechanics, a probability amplitude is a complex number whose modulus squared represents a probability or probability density. For example, the values taken by a normalised wave function ψ are amplitudes, since |ψ(x)|2 gives the probability density at position x. Probability amplitudes may also correspond to probabilities of discrete outcomes.
It means that the probability density function is symmetric about 0.
No. f is a letter of the Roman alphabet. It cannot be a probability density function.
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
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)
A probability density function.
See related link, In quantum mechanics, a probability amplitude is a complex number whose modulus squared represents a probability or probability density. For example, the values taken by a normalised wave function ψ are amplitudes, since |ψ(x)|2 gives the probability density at position x. Probability amplitudes may also correspond to probabilities of discrete outcomes.
Yes- the highest probability value is the mode. Let me clarify this answer: For a probability mass function for a discrete variables, the mode is the value with the highest probability as shown on the y axis. For a probability density function for continuous variables, the mode is the value with the highest probability density as shown on the y-axis.
It means that the probability density function is symmetric about 0.
A probability density function can be plotted for a single random variable.