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A convolution is a function defined on two functions f(.) and g(.). If the domains of these functions are continuous so that the convolution can be defined using an integral then the convolution is said to be continuous. If, on the other hand, the domaisn of the functions are discrete then the convolution would be defined as a sum and would be said to be discrete. For more information please see the wikipedia article about convolutions.
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What is the difference between a discrete and a continuous distribution?
A simple continuous distribution can take any value between two other values whereas a discrete distribution cannot.
What is the difference between discrete and cumulative distributions?
A discrete distribution is one in which the random variable can take only a limited number of values. A cumulative distribution, which can be discrete of continuous, is the sum (if discrete) or integral (if continuous) of the probabilities of all events for which the random variable is less than or equal to the given value.
What type of data has an infinite number of points between each measurement?
I think you are going for continuous variable, as compared with discrete variables.
Is a bar graph discrete or continuous?
It is both, a bar graph can be for discrete and continuous it depends on how you set out the chart. If it is for discrete data then you have to have a gap between each bar but on a continuous bar graph they are all next to each other WITHOUT any gaps. Also another way to discover if a bar graph is discrete or continuous the dicrete graph bars are labelled individually but on a continuous they are not labelled as such; there is a scale on the bottom axis. Hope this helps who ever needs it :D
Is the number of pregnancies a woman has had an example of discrete or continuous variable?
Discrete. You can't have 1.5 pregnancies. Or anything between 1 or 2. If you have had 1, your next is 2.
