Regression is a technique used to predict future values based on known values. For instance, linear regression allows us to predict what an unknown Y value will be, given a series of known X and Y’s, and a given X value. Given the following, it’s easy to see the pattern. But assuming no obvious pattern…
Tag: statistics
Correlation (Calculating Pearson’s r)
Correlation refers to the idea that two variables (x and y) impact each other. For instance, the grades in a statistics class may be related to, or correlated with the amount of time those students study. As study time goes up, grades go up. This would be a positive correlation. On the other hand, as…
Z-Scores
Z Scores were a concept I had trouble with in University. It’s actually not as difficult as they’re made out to be. I’ll spare you the complicated introduction (as I’m sure you got one from both your textbook and your Professor), but remember that z-scores show you the distance between your score and the mean,…
Dispersion and Variability (Standard Deviation)
The topics dispersion and variability (or variance) describes the “spread” of data in a distribution. This article explains how to compute the variance and the standard. The first measure of dispersion to look at is the variance. Let’s look at the data set below: X Values 4 5 2 7 Steps to Calculate Variance:…
Measures of Central Tendency
The measures of central tendency are processes for determining what the central value in a dataset is. The most common is the arithmetic average, or mean – so this value has come to be known as simply the average. The three measures of central tendency are mean, median and mode. Mean To calculate the mean…