Articles with this tag assume an intermediate knowledge within this category.
Leveraging Z-Score to Understand Data Dispersion In my Standard Deviation article I demonstrated how to use the squared variance to show the average distance each data point resides from the mean. While variance and standard deviation illustrate data dispersion from the mean in terms of their precise location in relation to the mean, Z-Score provides…
Statistics: Distributions – The Empirical Rule In my Distribution Shapes article, I discussed the different shapes most distributions of data would visually utilized, with symmetrical being the most common. These bell-shaped distributions demonstrate the “empirical rule” which demonstrates a relationship between data points and standard deviations placement in relation to the mean. The distribution below…
Understanding Causes of Skewed Distribution Shapes In my Distribution Shapes article I illustrates the three most common shapes founds with distributions – symmetrical, left-skewed, and right-skewed. Symmetrical distributions display data points equally on both sides because most of the values reside near the mean (average). This near-uniformity of data points with the average prevents the…
Isolating Patterns Based on Conditions In my Marginal Distributions article, I illustrated how to leverage a data set to isolate two marginal distributions in comparison with the grand total of all distributions, to arrive at specific distributions. This concept illustrates the concept of a conditional distribution in that a distribution is isolated based on a…
Isolating a Distribution’s Subset In my Joint Distributions article, I illustrated how to provide a data set using two (joint) distributions, with the Age Groups and Years distributions complementing each other. In this article I will demonstrate how to create a marginal distribution, which isolates one of the available distributions and measures it against the…
Using Foreknowledge of Data Set Changes to Understand the Effects In most data studies, the original data set is modified to tease-out certain patterns. Knowing how certain changes affect metrics may prove a very useful tool when communicating results to clients. In this example, I will begin with a simple data set illustrating disease diagnoses…
Visually Illustrating Bounds, Median, Range Box and Whisker Plot provides a very efficient method for communicating several measurements. To illustrate how to create a box and whisker plot, I’ll use a free website and Excel. First, I’ll use the following link to access the free website. Now that my data set is ready to use…
