It is an example of continuous variations.
Continuous variations have a wide range of possibilities. For example, your height is a continuous variation. There are many options (for example you could be 5'9, 4'6, 6'1) rather than an either/or situation. Discrete variations have only two possibilities. They can be thought of as "either/or" situations. For example, you can either roll your tongue or you can't. There is no grey area or in-between.
No. There are many common functions which are not discrete but the are not continuous everywhere. For example, 1/x is not continuous at x = 0 (it is not even defined there. Then there are curves with step jumps.
hair colour
How about f(x) = floor(x)? (On, say, [0,1].) It's monotone and therefore of bounded variation, but is not Lipschitz continuous (or even continuous).
AnswerDiscrete variation refers to differences in characteristics that have a defined form. You can think of it as being either/or.For example. Your earlobes are either attached or they are not. Or whether or not you can roll your tongue.Continuous variation comes in a range of forms.For example. Height - is not a set number or another.
Continuous variations have a wide range of possibilities. For example, your height is a continuous variation. There are many options (for example you could be 5'9, 4'6, 6'1) rather than an either/or situation. Discrete variations have only two possibilities. They can be thought of as "either/or" situations. For example, you can either roll your tongue or you can't. There is no grey area or in-between.
No. There are many common functions which are not discrete but the are not continuous everywhere. For example, 1/x is not continuous at x = 0 (it is not even defined there. Then there are curves with step jumps.
hair colour
blood group
This is a typical kind of continuous variation which is controlled by polygenes.
How about f(x) = floor(x)? (On, say, [0,1].) It's monotone and therefore of bounded variation, but is not Lipschitz continuous (or even continuous).
its continuous because if it was discrete i could measure it right now but its actually over time. For example: if my doctor wants to weigh me ,he will weigh me once and then weigh me again in like 1 week or so
In signal processing, sampling is the reduction of a continuous signal to a discrete signal. A common example is the conversion of a sound wave (a continuous signal) to a sequence of samples (a discrete-time signal).
no, as a flower is either for example blue or white, and cannot be something in between, thus its discontinuous variation.
Discrete. You can't have 1.5 pregnancies. Or anything between 1 or 2. If you have had 1, your next is 2.
The weight of an object is an example of the physical properties of the object and the effect of gravity on a mass.
A continuous signal is one that is measured over a time axis and has a value defined at every instance. The real world is continuous (ie. analog). A discrete signal is one that is defined at integers, and thus is undefined in between samples (digital is an example of a discrete signal, but discrete does not have to imply digital). Instead of a time axis, a discrete signal is gathered over a sampling axis. Discrete signals are usually denoted by x[k] or x[n], a continuous signal is x(t) for example. Laplace transforms are used for continuous analysis, Z-transforms are used for discrete analysis. Fourier transforms can be used for either.