1.1 - Classifying Statistics
1.1 - Classifying StatisticsLet’s get to know some of the descriptive statistics. The first challenge is determining what kind of data you are dealing with. There are generally two main types of data, qualitative and quantitative. Qualitative data is typically words, but could also be images or other media, we will refer to this data in this course as categorical. Qualitative data may be labeled with numbers allowing this type of data to be analyzed using some of the techniques in the course. Maria might encounter some qualitative data in her work by labeling some of the mental health diagnoses (depression might be a “1”; anxiety a “2”). Note how these numerical labels are arbitrary. On the other hand, quantitative data is the focus of this course and is numerical. If Maria counts the number of patients seen each day, this data is quantitative.
Categorical variables are those that provide groupings that have no logical order, or a logical order. Quantitative variables have numerical values with meaningful intervals, but are further divided into different sub types.
Quantitative variables may be discrete or continuous. Discrete variables can only take on a limited number of values (e.g., only whole numbers) while continuous variables can take on any value and any value between two values (e.g., out to an infinite number of decimal places).
To summarize...
- Categorical Variable
- Names or labels (i.e., categories) with no logical order or with a logical order but inconsistent differences between groups, also known as qualitative.
- Quantitative Variable
- Numerical values with magnitudes that can be placed in a meaningful order with consistent intervals, also known as numerical.
- Continuous Variable
- Characteristic that varies and can take on any value and any value between values
- Discrete Variable
- Characteristic that varies and can only take on a set number of values
Example 1-1: Weight
If a child admitted to Maria’s program is weighed upon admission, this weight is a quantitative variable because it takes on numerical values with meaningful magnitudes. It is a continuous variable because, theoretically, weight could take on any value. Any value between any two values is a possibility.
Example 1-2: Favorite Ice Cream Flavor
If each child at Maria’s organization is offered an ice cream cone, there may be three choices of flavors, chocolate, vanilla, or strawberry. The ice cream flavor is a categorical variable because the different flavors are categories with no meaningful order.
Example 1-3: Birth Location
A survey asks “On which continent were you born?” This is a categorical variable because the different continents represent categories without a meaningful order of magnitudes.