Skip to main content
Chemistry LibreTexts

3.23: Categorical vs. Quantitative Data

  • Page ID
    251281
  • \( \newcommand{\vecs}[1]{\overset { \scriptstyle \rightharpoonup} {\mathbf{#1}} } \) \( \newcommand{\vecd}[1]{\overset{-\!-\!\rightharpoonup}{\vphantom{a}\smash {#1}}} \)\(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\) \(\newcommand{\id}{\mathrm{id}}\) \( \newcommand{\Span}{\mathrm{span}}\) \( \newcommand{\kernel}{\mathrm{null}\,}\) \( \newcommand{\range}{\mathrm{range}\,}\) \( \newcommand{\RealPart}{\mathrm{Re}}\) \( \newcommand{\ImaginaryPart}{\mathrm{Im}}\) \( \newcommand{\Argument}{\mathrm{Arg}}\) \( \newcommand{\norm}[1]{\| #1 \|}\) \( \newcommand{\inner}[2]{\langle #1, #2 \rangle}\) \( \newcommand{\Span}{\mathrm{span}}\)\(\newcommand{\AA}{\unicode[.8,0]{x212B}}\)

     

    Learning Objectives

    • Distinguish between quantitative and categorical variables in context.

    Data consist of individuals and variables that give us information about those individuals. An individual can be an object or a person. A variable is an attribute, such as a measurement or a label.

    Example

    Medical Records

    This dataset is from a medical study. In this study, researchers wanted to identify variables connected to low birth weights.

    Dataset showing variables associated with low birth weight

    In this example, the individuals are the patients (the mothers). There are six variables in this dataset:

    • Mother’s age at delivery (years)
    • Mother’s weight prior to pregnancy (pounds)
    • Whether mother smoked during pregnancy (yes, no)
    • Number of doctor visits during first trimester of pregnancy
    • Mother’s race (Caucasian, African American, Asian, etc.)
    • Baby’s birth weight (grams)

    There are two types of variables: quantitative and categorical.

    • Categorical variables take category or label values and place an individual into one of several groups. Each observation can be placed in only one category, and the categories are mutually exclusive. In our example of medical records, smoking is a categorical variable, with two groups, since each participant can be categorized only as either a nonsmoker or a smoker. Gender and race are the two other categorical variables in our medical records example.
    • Quantitative variables take numerical values and represent some kind of measurement. In our medical example, age is an example of a quantitative variable because it can take on multiple numerical values. It also makes sense to think about it in numerical form; that is, a person can be 18 years old or 80 years old. Weight and height are also examples of quantitative variables.

    Learn By Doing

    We took a random sample from the 2000 US Census. Here is part of the dataset.

    Census 2000 dataset that shows average family size and annual income by zip codes within stateshttps://assessments.lumenlearning.co...sessments/3411

    https://assessments.lumenlearning.co...sessments/3412

    Learn By Doing

    Consumer Reports analyzed a dataset of 77 breakfast cereals. Here is a part of the dataset.

    (Note: Consumer Reports is an non-profit organization that rates products in an effort to help consumers make informed decisions.)

    Data set of seven breakfast cereals that shows manufacturer, where on the grocery store shelf they are located, their target (adult of child), and percentage of calories, sodium and fat per serving.

    https://assessments.lumenlearning.co...sessments/3415

    https://assessments.lumenlearning.co...sessments/3416

    CC licensed content, Shared previously

    3.23: Categorical vs. Quantitative Data is shared under a not declared license and was authored, remixed, and/or curated by LibreTexts.

    • Was this article helpful?