Normal distributions review. Google Classroom. Normal distributions come up time and time again in statistics. A normal distribution has some interesting properties: it has a bell shape, the mean and median are equal, and 68% of the data falls within 1 standard deviation. The normal distribution is a probability distribution, so the total area under the curve is always 1 or 100%. The formula for the normal probability density function looks fairly complicated. But to use it, you only need to know the population mean and standard deviation. Recognize and use the standard normal probability distribution. A special continuous distribution, called normal, is the most common and therefore most important of all the distributions. It is widely used and even more widely abused. Its graph is bell-shaped. You see the bell curve in almost all disciplines. Many variables are nearly normal, but none are exactly normal. Thus the normal distribution, while not perfect for any single problem, is very useful for a variety of problems. We will use it in data exploration and to solve important problems in statistics. The Normal distribution is also known as Gaussian or Gauss distribution. Many groups follow this type of pattern. That's why it's widely used in business, statistics, and in government bodies like the FDA: Heights of people. Measurement errors. Blood pressure. Points on a test. A normal distribution is significant in statistics and is often used in the natural sciences and social arts to describe real-valued random variables whose distributions are unknown. Q4 What are the characteristics of a normal distribution? Ebl4J.

what is normal distribution used for