Opening the book…
To evaluate the quality of a continuous distribution, you are looking for something specific to improve its quality. What you want is a normal distribution when there is a bell-shaped curve and scores are evenly dispersed around the mean.
By the way, good luck trying to find a bell-shaped curve. It is rare that you get a bell-shaped curve that represents a normal distribution. That means that even if a distribution does not look like a bell-shaped curve, it's probably close enough to resemble a normal distribution.
To evaluate the distribution of continuous variables, first create a histogram. A histogram is a graphic representation of the frequency distribution. The histogram answers the following questions. What is being distributed? The scores along the continuum of the variable range. How many participants have a particular score along the continuous variable? How do we distribute the variable? First, we distribute it along the x-axis. The x-axis displays the range of the variable or all possible scores. Who is in this distribution? Along the Y axis, the number of participants with a particular score is shown.
This page titled 4.5: Evaluating the Quality of Frequency Distributions was last modified on Fri, 01 Aug 2025 04:10:25 GMT and is shared under a CC BY 4.0 license and was authored, remixed, and/or curated by Peter Ji.
The book could not be loaded just now.