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Discrete and Continuous Data. ... or Numerical (numbers). And Numerical Data can be Discrete or Continuous: Discrete data is counted, Continuous data is measured . Discrete Data. Discrete Data can only take certain values. Example: the number of students in a class. We can't have half a student! Example: the results of rolling 2 dice. Only has ...


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.


Discrete data has a specific value, while continuous data can be divided infinitely. Learning Outcome Once you are finished with this lesson, you should be able to identify and describe the two ...


Statistics and data management sciences require a deep understanding of what is the difference between discrete and continuous data set and variables. The similarity is that both of them are the two types of quantitative data also called numerical data.


1.2 - Discrete Data Types and Examples. Printer-friendly version ... Continuous variables grouped into small number of categories, e.g., income grouped into subsets, blood pressure levels (normal, high-normal etc) We we learn and evaluate mostly parametric models for these responses.


Discrete and Continuous Data are two ways of classifying data used in cartography and GIS to portray spatial elements and applications. All the data featured in maps and models are either discrete or continuous. Discrete data may only be recorded or reported as certain values while continuous data may be any value within a certain range.


Time to complete a task is continuous since it could take 178.8977687 seconds. Time forms an interval from 0 to infinity. You can usually tell the difference between discrete and continuous data because discrete usually can be preceded by "number of...". Here are some examples of discrete and continuous data.


Discrete data refers to specific and distinct values, while continuous data are values within a bounded or boundless interval. Discrete data and continuous data are the two types of numerical data used in the field of statistics.


Discrete data are whole-number counts of distinctly categorizable items, generally, in finite quantities. While such data can potentially reach infinity, none of the values in a data set can be subdivided or broken down into a smaller unit and add additional meaning.


For example, you can measure the height of your kids at progressively more precise scales—meters, centimeters, millimeters, and beyond—so height is continuous data. If I tally the number of individual Jujubes in a box, that number is a piece of discrete data.