Properties of a normal distribution
There are a few things that differentiate a normal distribution from other distributions. For instance:
- The mean, median, and mode are all equal
- The curve is symmetrical around the mean (at the center)
- Half of the values displayed on the curve are to the right of the mean and another half is to the left
- The area under the curve is always one
In addition to the above properties, a normal distribution curve contains skewness and kurtosis, coefficients used to measure the symmetry of the distribution, and the thickness of the ends of the tails respectively.
Parameters of normal distribution
A normal distribution has two main parameters: the mean and standard deviation. These two parameters determine the probabilities and shape of the distribution. When changes are applied to the parameter values, the shape of the distribution also changes.
Practical applications of normal distribution models
The normal distribution can help you find out which subjects you are good at and which ones you need to put in a little more work. When you score a higher grade in one subject and score poorer in another, you will certainly think that you scored higher in this one subject because you are better at it, but that’s not always true. The only time you can say that you are good at a certain subject is if the mark you get has a specific number of standard deviations over, or rather, above the mean. As mentioned earlier, standard deviation shows you how data is distributed around the mean. It enables you to make comparisons between different distributions including different data types and means. If you score 95 in Chemistry and 90 in Math, for instance, you may think you are good at Chemistry than you are in Math. But in Chemistry, the score is one standard deviation over the mean, while in Math, it is two standard deviations over the mean. This shows that your score in Math is way higher than what most students scored. Looking at the results of the standard deviation you actually scored better in Chemistry than in Math.