http://www.ck12.org Chapter 4. Standard Distributions - Basic
But what about if we were talking about 500 repetitions? Now we would type in:
Notice as we increase the number of repetitions, we are getting closer and closer to the normal distribution from
the beginning of this chapter. For data that is actually normal distributed, the sample size can be any size. So, for
example, you could collect the marks from a class of students(n= 30 )and find that these are normally distributed.
For binomial distributions, the sample size tends to be much larger.
Another type of distribution is calledexponential distribution. If you remember, both normal distribution and
binomial distribution dealt with discrete data. Discrete variables are individualized data points such as heads or
tails, marks on a test, a baby being a boy or a girl, rolls on a die, etc. Essentially, these are set numbers being an
either-or choice. With exponential distributions, however, the data are considered continuous. Continuous variables
have an infinite number of groupings depending on what kind of scale you use. Say, for example, you surveyed
your class and asked them how long it took them to walk to school. Your scale could be in minutes, in minutes and
seconds, in minutes, seconds, and fractions of a second (which may seem unreasonable if you are not an Olympic
Athlete). Regardless, the time measurement itself is a continuous variable. Look at the two graphs below just to see
the difference between a graph of a discrete variable and the graph of a continuous variable.
For exponential distributions, the continuous data graph would change to look more like the following: