Height and weight are numrical or categorical attribute
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When working with statistics, it’s important to recognize the different types of data: numerical (discrete and continuous), categorical, and ordinal. Data are the actual pieces of information that you collect through your study. For example, if you ask five of your friends how many pets they own, they might give you the following data: 0, 2, 1, 4, 18. (The fifth friend might count each of her aquarium fish as a separate pet.) Not all data are numbers; let’s say you also record the gender of each of your friends, getting the following data: male, male, female, male, female.
Most data fall into one of two groups: numerical or categorical.
Numerical data. These data have meaning as a measurement, such as a person’s height, weight, IQ, or blood pressure; or they’re a count, such as the number of stock shares a person owns, how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep. (Statisticians also call numerical data quantitative data.)
Numerical data can be further broken into two types: discrete and continuous.
Categorical data: Categorical data represent characteristics such as a person’s gender, marital status, hometown, or the types of movies they like. Categorical data can take on numerical values (such as “1” indicating male and “2” indicating female), but those numbers don’t have mathematical meaning. You couldn’t add them together, for example. (Other names for categorical data are qualitative data, or Yes/No data.)
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Most data fall into one of two groups: numerical or categorical.
Numerical data. These data have meaning as a measurement, such as a person’s height, weight, IQ, or blood pressure; or they’re a count, such as the number of stock shares a person owns, how many teeth a dog has, or how many pages you can read of your favorite book before you fall asleep. (Statisticians also call numerical data quantitative data.)
Numerical data can be further broken into two types: discrete and continuous.
Categorical data: Categorical data represent characteristics such as a person’s gender, marital status, hometown, or the types of movies they like. Categorical data can take on numerical values (such as “1” indicating male and “2” indicating female), but those numbers don’t have mathematical meaning. You couldn’t add them together, for example. (Other names for categorical data are qualitative data, or Yes/No data.)
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