1.3:
How Data are Classified: Numerical Data
Data that are countable or measurable in specific units are called numerical data or quantitative data.
For example, one can count the number of children to a couple or calculate how many liters of milk a cow produces in a month.
If one carefully observes, data on the number of children to a couple is a finite number that could be 1, 2, or even 5. Such quantitative data with finite measures or countable numbers is called discrete data. Another example is the number of fish in a pond.
Conversely, quantitative data, which can take up infinite value over a continuous span, including decimals or fractions, are called continuous data.
In the previous example, the cow may have produced 54.8, 75.5, or 99.56 liters in a month, a continuous range of values between 0 to 100.
1.3:
How Data are Classified: Numerical Data
Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical values are called discrete data. For instance, the number of phone calls received for each day of the week can be zero, one, two, or three, a whole number.
Data that include fractions, decimals, or irrational numbers are called continuous quantitative data. Continuous data are often the results of measurements like length, weight, or time. For example, the phone calls made in a day can have any numerical values such as 2.4 minutes, 7.5 minutes, or 11.0 minutes. The number of books that students carry in their backpacks is an example of discrete data, while the weight of the backpacks carried by the students is an example of continuous data.
This text is adapted from Openstax, Introductory Statistics, Section 1.1 Definitions of Statistics, Probability, and Key Terms