What is the difference between discrete data and continuous data?
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Discrete data can only take particular values. There may potentially be an infinite number of those values, but each is distinct and there's no grey area in between. Discrete data can be numeric -- like numbers of apples -- but it can also be categorical -- like red or blue, or male or female, or good or bad.
Continuous data are not restricted to defined separate values, but can occupy any value over a continuous range. Between any two continuous data values there may be an infinite number of others. Continuous data are always essentially numeric.
It sometimes makes sense to treat numeric data that is properly of one type as being of the other. For example, something like height is continuous, but often we don't really care too much about tiny differences and instead group heights into a number of discrete bins. Conversely, if we're counting large amounts of some discrete entity -- grains of rice, or termites, or pennies in the economy -- we may choose not to think of 2,000,006 and 2,000,008 as crucially different values but instead as nearby points on an approximate continuum.
It can also sometimes be useful to treat numeric data as categorical, eg: underweight, normal, obese. This is usually just another kind of binning.
It seldom makes sense to consider categorical data as continuous.
Data is always discrete. Given a sample of
Data on a variable are typically assumed to be drawn from a random variable. The random variable is continuous over a range if there is an infinite number of possible values that the variable can take between any two different points in the range. For example, height, weight, and time are typically assumed to be continuous. Of course, any measurement of these variables will be finitely accurate and in some sense discrete.
It is useful to distinguish between ordered (i.e., ordinal), unordered (i.e., nominal),
Some introductory textbooks confuse a continuous variable with a numeric variable. For example, a score on a computer game is discrete even though it is numeric.
Some introductory textbooks confuse a ratio variable with continuous variables. A count variable is a ratio variable, but it is not continuous.
In actual practice, a variable is often treated as continuous when it can take on a sufficiently large number of different values.
Temperatures are continuous. It can be 23 degrees, 23.1 degrees, 23.100004 degrees.
Gender is discrete. You can only be male or female (insert san francisco joke here). Something you would represent with a whole number like 0, 1, 2, etc
The difference is important as many statistical and data mining algorithms can handle one type but not the other. For example in regular regression, the Y must be continuous. In logistic regression the Y is discrete.
In the case of database, we would always store the data in discrete even the nature of the data is continuous. Why should I emphasize the nature of data? We should take the distribution of data that could help us to analyze the data. IF the nature of data is continuous, I suggest you to use them by continuous analysis.
Take an example of continuous and discrete: MP3. Even the type of "sound" is analogy, if stored by digital format. We should analyze it always in a analogy way.
Discrete Data can only take certain values.
Example: the number of students in a class (you can't have half a student).
Continuous Data is data that can take any value (within a range)
Discrete data can take on only integer values whereas continuous data can take on any value. For instance the number of cancer patients treated by a hospital each year is discrete but your weight is continuous. Some data are continuous but measured in a discrete way e.g. your age. It is common to report your age as say, 31.
Discrete data take particular values, while continuous data are not restricted to separate values.
Discrete data are distinct and there is no grey area in between, while continuous data occupy any value over a continuous data value.
Discrete data perticularly talks about the finite values and continuous data talks about ifinite values.....
protected by Community♦ Feb 3 '15 at 21:13
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