4.1. Normal Distributions http://www.ck12.org
4.1 Normal Distributions
Here you’ll learn how to distinguish between graphs of discrete and continuous data. You’ll also become familiar
with the properties of a normal distribution and determine if a specific data set approximates a normal distribution.
Have you ever heard your teacher say that he or she was going to "grade on a curve"? If 100 people take an exam,
the data of their scores can be plotted. How would you expect this plot to look? Suppose that the highest score is
75% and the lowest score is 15%. Your score was the highest score! Your teacher is going to "grade on the curve"
and you’ll receive an A for this exam. Your friend is upset because his score was 28%. Based on this curve will your
friend pass the exam?
Watch This
First watch this video to learn about normal distributions.
MEDIA
Click image to the left for more content.CK-12 Foundation: Chapter4NormalDistributionsA
Then watch this video to see some examples.
MEDIA
Click image to the left for more content.CK-12 Foundation: Chapter4NormalDistributionsB
Guidance
Previously you’ve spent some time learning about probability distributions. Adistribution, itself, is simply a
description of the possible values of a random variable and the possible occurrences of these values. Remember that
probability distributions show you all the possible values of your variable (X), and the probability associated with
each of these values(P(X)). You were also introduced to the concept of binomial distributions, or distributions of
experiments where there are a fixed number of successes inX(random variable) trials, and each trial is independent
of the other. In addition, you were introduced to binomial distributions in order to compare them with multinomial
distributions. Remember that multinomial distributions involve experiments where the number of possible outcomes
is greater than 2, and the probability is calculated for each outcome for each trial.