AP Notes, Outlines, Study Guides, Vocabulary, Practice Exams and more!

Statistics

Forum reference: 
AP Statistics
Book page: 
http://course-notes.org/Statistics

Nonparametric Statistics

Nonparametric statistics is the field of statistical inference
where no assumption is made about the probability distribution of
the population under study. While most sample tests assume that
the parent population(s) of the sample data is (are) normally
distributed, the statistical methods of nonparametric statistics
are valid for any probability distribution that the population
may have (with certain exceptions).

Sampling Theory

Sampling theory is the field of statistics that is involved
with the collection, analysis and interpretation of data gathered
from random samples of a population under study. The application
of sampling theory is concerned not only with the proper
selection of observations from the population that will
constitute the random sample; it also involves the use of
probability theory, along with prior knowledge about the
population parameters, to analyze the data from the random sample
and develop conclusions from the analysis. The normal

Discrete Probability Distributions

A discrete probability distribution is a
function with a domain whose elements are the discrete values
that a discrete random variable can assume, and a range whose
elements are the probabilities associated with the values in the
domain. The domain of a discrete probability distribution
consists of the sample points of a discrete sample space. The sum
of all the probability values in the range is equal to 1. The
mean and variance of a discrete probability distribution are the

Probability Distributions

The probability distribution of a random
variable is a function whose domain contains the values that the
random variable can assume, and whose range is a set of values
associated with the probabilities of the elements of the domain.
The probability distribution of a discrete random variable is
called a discrete probability distribution,
while the probability distribution of a continuous random
variable is called a continuous probability distribution.

Random Variables

A random variable is a function that can take
on values corresponding to a sample point in a sample space. As
each sample point is associated with a probability value, random
variables assumes its values with a certain probability that
depends on the sample point on which the value is based. A random
variable that is defined over a discrete sample space has a
finite or countable number of possible values and is called a discrete
random variable. A random variable that is defined over

Pages

Subscribe to RSS - Statistics

Need Help?

We hope your visit has been a productive one. If you're having any problems, or would like to give some feedback, we'd love to hear from you.

For general help, questions, and suggestions, try our dedicated support forums.

If you need to contact the Course-Notes.Org web experience team, please use our contact form.

Need Notes?

While we strive to provide the most comprehensive notes for as many high school textbooks as possible, there are certainly going to be some that we miss. Drop us a note and let us know which textbooks you need. Be sure to include which edition of the textbook you are using! If we see enough demand, we'll do whatever we can to get those notes up on the site for you!