Statistical Concepts
Normal distributions are bell curves
Normal distributions are an arrangement of data scores which cluster around the mean. A normal distribution is unimodal, symmetric, and commonly referred to as “bell shaped”.
Example
If you measured the height of 100 students in a psychology class at Trent University, the majority of students would be of average height, the number of people who are a taller and shorter than average would be fairly equal, and only a very small portion of people would be extremely tall and extremely short.
Skewness
Follow the tail
Skewness is the degree to which a distribution is asymmetrical. A distribution can be either positively skewed or negatively skewed.
A good way to remember which skewed distribution is which, is to follow the tail. The tail of a negatively skewed distribution points left toward the negative side of the histogram, whereas the tail of the positively skewed distribution points right toward the positive side of the histogram.
Example
A researcher conducts a survey with group of elderly people about their age of retirement. Because the majority of people retire in their mid 60s or older, the distribution would be negatively skewed. The data scores would be clustered toward the positive side of the histogram, with the tail of the distribution pointing toward the negative side of the histogram.
