Observational Units and Variables
The next step in a statistical investigation is to decide what to measure and to collect the data. Data are often shown as a long list of information about a group of individuals, animals, or objects.
In any study, the observational units serve as the foundation for data collection. It is these units—be they people, animals, or objects—that we observe and from which we gather data.
observational units
The group of individuals, animals, or objects who are being measured or surveyed in a study are the observational units.
The specific details we record about each of these units, such as age, weight, or color, are known as variables. These variables are what we analyze to understand patterns, draw conclusions, or test hypotheses.
variables
The characteristics of the observational units in a study are recorded as variables.
Qualitative and Quantitative Data
Data are the actual values of the variable. They may be numbers or they may be words. As such, data can be categorized as qualitative or quantitative data.
qualitative data
Qualitative data are the result of categorizing or describing attributes of a population. Hair color, blood type, ethnic group, the car a person drives, and the street a person lives on are examples of qualitative data.
Qualitative data are also often called categorical data.
Qualitative data are generally described by words or letters. For instance, hair color might be black, dark brown, light brown, blonde, gray, or red. Blood type might be AB+, O-, or B+.
quantitative data
- Quantitative data are the result of counting or measuring attributes of a population. Amount of money, pulse rate, weight, number of people living in your town, and number of students who take statistics are examples of quantitative data.
- Quantitative discrete data are the result of counting. If you count the number of phone calls you receive for each day of the week, you might get values such as [latex]0, 1, 2, \mathrm{or} \ 3[/latex].
- Quantitative continuous data may also include fractions, decimals, or irrational numbers. Continuous data are often the results of measurements like lengths, weights, or times like a list of the lengths in minutes for all the phone calls that you make in a week, with data like [latex]2.4, 7.5, \mathrm{or} \ 11.0[/latex].
Quantitative data are always numbers.
