Cat has a master's degree in education and is currently working on her Ph.D. Cite this lesson Categorical data is a type of data that can be divided or classified into groups. Understand the definition and examples of categorical data, learn to distinguish categorical data from quantitative ...
Categorical data, on the other hand, is descriptive and conceptual and cannot be directly manipulated with mathematical operations. Colors, product models, and email addresses are common examples. Your bank account number, describing the weather as hot, mild, or cold, and classifying the results...
Learn how ANOVA can help you understand your research data, and how to simply set up your very first ANOVA test.
Learn exactly what interval data is, what it’s used for, and how it’s analyzed, complete with handy examples. Check out the full guide here.
What Is Ordinal Data Used For? Ordinal data, when well and consistently collected, allows researchers to bring statistical insight to bear on a variety of topics not broachable by more precise forms of scientific measurement. Important questions concerning overall contentment in life, subjective interp...
Bar charts are used to plot categorical data against discrete values. Categorical data refers to data that is not numeric, and it’s often used to describe certain traits or characteristics. Some examples of categorical data include things like education level (e.g. high school, undergrad, or ...
Rasters representing thematic data can be derived from analyzing other data. A common analysis application is classifying a satellite image into land cover categories. Basically, this activity groups the values of multispectral data into classes (such as vegetation type) and assigns a categorical value...
Type I Error (False Positive): This error occurs when you reject the null hypothesis even though it’s actually true. In simpler terms, you’re finding a significant result where there isn’t one. It’s like a false alarm—your data might suggest a difference or effect, but it’s actua...
Overall, there are four types of data used in machine learning: numeric, categorical (e.g., those wind speeds and temperatures from the weather example, which define certain characteristics of whatever is being analyzed), time series and text. Structured data helps convert all four from free-te...
Data can also be categorical, which means it has a fixed number of data values, like a person's gender. Data that is both time- and space-bound is spread out in a random way. Discrete distributions make it easier to look at discrete values.Continuous DataThese...