ASSIGNMENT #1 Review:
Discrete Random Variable is when the outcome is countable.
As long as the outcome is
similar you can use the distribution.
Variables typically serve as a form of measurement.
When dealing with a random variable you are concerned with 1.) possible outcomes and
also 2.) probability.
Table below shows probability distribution.
X 1
2
3
4
5
6

Probability (will come from hypothesis or experience)
.1
.2
.4
.1
.1
.1
Mean = expected value.
(point of value for possible outcome representation).
Significance of the mean is that you weigh each value the same when computing it.
Variance= expected squared deviation from the mean
When dealing with statistics the concept refers to the idea.
Method refers to how you use
the data to get what you need (i.e. computing the mean).
E(X) = 1*.1 + 2*.2 + 3*.4 + 4*.1+5*.1+6*.1
MINITAB:
Session editor
Editor
edit commands.
Use “let” command, c3 =c1*c2
Print k1 is the command in order to get K value.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
This is the end of the preview.
Sign up
to
access the rest of the document.
 Spring '08
 Chen
 Probability theory, editor, discrete random variable, shows probability distribution, possible outcome representation

Click to edit the document details