Continuous data often involves measurements like height, weight, or time.
It can be represented on a number line and can take any value within a range.
In statistics, continuous variables are typically analyzed using techniques such as histograms and density plots.
Examples include temperature readings, lengths of objects, and times to complete a task.
The distinction between continuous and discrete data is crucial in determining the appropriate statistical methods for analysis.
Review Questions
What is an example of continuous data?
How does continuous data differ from discrete data?
What types of plots are commonly used to represent continuous data?
Related terms
Discrete Data: Data that can only take specific values and cannot be made more precise. Examples include the number of students in a class or the result of rolling a die.
Histogram: A graphical representation used to visualize the distribution of a dataset by showing the frequency of different ranges of continuous data.
Density Plot: A smoothed version of a histogram that estimates the probability density function of continuous data.