The probability distribution function (pdf) is defined over a domain which contains at least one interval in which the pdf is positive for all values.
Usually the domain is either the whole of the real numbers or the positive real numbers, but it can be a finite interval: for example, the uniform continuous distribution.
Also, trivially,
the pdf is always non-negative,
the integral of the pdf, over the whole real line, equals 1.
Yes, the normal distribution, standard or not is always continuous.
Continuous
It is continuous.
Yes
No, it's a continuous distribution.
The normal distribution is always continuous.
If the question is asking if a continuous distribution can be converted to a discrete distribution, the answer is yes. Your age has a continuous distribution but in most cases, the information is recorded and analysed as if it were the whole number of years - a discrete distribution.
Yes, the normal distribution, standard or not is always continuous.
Continuous
It is continuous.
No, it is continuous.
Yes.
Yes
No, it's a continuous distribution.
Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.
discrete distribution is the distribution that can use the value of a whole number only while continuous distribution is the distribution that can assume any value between two numbers.
The power distribution is a continuous distribution with a parameter that we will denote k.