9.7 Blog Post

9.7: Probability, Dude

Merriam-Webster (rough riders don’t use dictionary.com) defines probability as the ratio
of the number of outcomes in an exhaustive set of equally likely outcomes that produce
a given event to the total number of possible outcomes or the chance that a given event
will occur.

Definin’ Some Termz:

Experiment-activity under consideration
Outcome-Each possible observation
Sample space/Outcome set-set of possible outcomes
Event-subset of a sample space

No Mo Termz

How ‘Bout We Do Some Scenarios???

Lets suppose you’re holding a coin. The type of coin isn’t vital, but lets call it a quarter,
cause quarters are big and yeah. So you’re ready to flip that coin and you ask yourself,
what are the chances that this quarter will land with Mr. Washington looking up at me? If
you are seriously thinking about the answer to this question, you probably need to re-
evaluate your life, but this is just an example so stop nit picking my flawless and
awesome blog post. The point is that the CHANCE you’re trying to calculate is the
PROBABILITY that the quarter will land heads up. You do so by creating a ratio of the
number of favorable outcomes (heads), divided by the number of possible outcomes
(heads and tails). This gives you ½. That’s easy, right? YEAH! But, I doubt Thad will put
it on a test because he likes to use his green pen.

Lets look at a trickier situation, shall we? Say you got Drew’s left shoe, and a six sided
die. The shoe can land either laces up or sole up. If you were to flip the shoe and then
role the die, what is the probability that you get laces and a 2? Lets break it down,
dawg. You gotta ½ chance of flippin’ a lace, right? Of course I’m right. Then, you would
multiply that by the ratio of favorable die outcomes (1) over total possible die outcomes
(6). Thus giving you a 1/12 shot of gettin’ laces and a 2. Done. Next.

Just throwing this out there… P(A)= the probability of A

Almost forgot, mutually exclusive means that two sample spaces do not share a
common event (usin’ dem termz).

Bring in the formulas!!!!!

P(A U B)= P(A) + P(B)*
P(A U B)= P(A) + P(B) - P(A “upside down U” B)
P(A “upside down U” B)= P(A) x P(B)**

Also, independent means that the events don’t influence each other, like how flipping
Barton’s shoe doesn’t effect the roll that the die will land on.

Now we get off track…

http://www.youtube.com/watch?v=eVtDSFgeqPY

http://www.youtube.com/watch?v=jsKpazuC0RY

This is too help Barton and Pete learn how to count:

http://www.youtube.com/watch?feature=endscreen&NR=1&v=85M1yxIcHpw

Back on task! YAY!

Complements are cool too. The complement of event A are all of the possible outcomes
in the sample space that are not in A. I’m tired so I’m not going to explain it in more
detail. The book does an okay job.
A’= Complement A
P(A’)= 1- P(A)

*Only if A&B are mutually exclusive
**Only if A&B are independent

My Closing Statement.

By now you have realized that this is the greatest blog post of all time, followed closely
by all of my other blog post, and then Oran’s famous “I’m going to be as creepy as
possible” post of 2010. I’m going to be completely honest, and I think I speak for
everyone when I say, I am pretty damn impressive.

Pete *****

Barton *****

Seaglass can’t do maths

Austin’s cool

Geller’s too smart

Thad’s a beast

Barton *****

And insert Noah’s blog post here:

I was just too tired to write this blog post. I am sorry that I could not supplement
you with more maths knowledge. Maths is forever.

NNNNNNNNNNNNOOOOOOOOOOOOOAAAAAAAAAAAAAHHHHHH!!!!!!!!!!!

K bye.