8/21/2017

## Course Info

• There will be NO curving of individual exam grades
• A student must earn a minimum of 60% on AT LEAST ONE of the 3 exams in order to pass this class.
A 90-100
B 80-89
C 70-79
D 60-69
F below 60

## Quiz

• 8 are scheduled
• Close book and close notes
• The lowest quiz will be dropped
• Make-up quiz
• Official documented University business or a documented illness

## Homework

• 5 assignments
• Due at the begining of class
• Late homework will NOT be accepted
• Must be handwritten or typed using mathematical notation.
• Each homework is worth 25 points, NO homeworks are dropped.

## Exams

• Two evening exams from 8:00 – 9:30 pm
• Tueday 9/26/17
• Thursday 11/2/17
• A final exam, during the day during final exam week
• Close book and close notes
• Items allowed
• pencils
• erasers
• a scientific calculator (must not have capability to do integration),
• one-page cheat sheet for mid-terms and two-page for the final,
• Show a photo ID to your instructor

## Cheat sheet

• 8 1⁄2 $$\times$$ 11
• Handwritten in your own writing
• Both sides
• Handing in your cheat sheet at the end of the exam is required
• Use of printed or photocopied material on a cheat sheet is prohibited and considered cheating in this course

## Emergency

• If you hear a fire alarm inside, proceed outside
• If you hear a siren outside, proceed inside
• Fire emergency:
• immediately suspend class, evacuate the building, and proceed outdoors
• do not use the elevator
• meet outside by fountain near John Purdue’s grave
• suspend class and shelter in interior hallway on $$1_{st}$$ floor
• SHELTER IN PLACE
• suspend class and shelter in the classroom
• shutting the door and turning off the lights

## Probability Theory

• Probability theory is the study of randomness and all things associated with randomness

## Key concepts

• Random Experiment: an action whose outcome cannot be predicted with certainty beforehand - drawing a card
• rolling a die
• flipping a coin
• Potential Outcome: One specific result from a random experiment

• Event: a collection of some outcomes
• empty set $$\Phi$$: no outcomes
• sample space $$S$$: consists of all outcomes

## Examples

• flipping a coin
• potential outcomes
• sample space
• events
• roll a regular dice
• potential outcomes
• sample space
• events
• greater than 3
• get an odd number
• greater than 7

## Subset

• Event A is a subset of event B, written $$A \subset B$$, if every outcome in A is also an outcome in B

• roll a dice:
• A: the roll is 2
• B: the roll is event number

## Probability of Events

• Probability: the proportion of times the event occurs in independent repetitions of the random experiment in the long run
• $$P(E) = \frac{|E|}{n}$$
• The probability of event E is the number of times an outcome in E occurs divided by the number of experiment repetitions

## Equally likely framework

• Any individual outcome in $$S$$ is equally likely to occur
• $$P(E) = \frac{|E|}{|S|}$$
• If all outcomes are equally likely, then then probability of event E is the number of outcomes in E divided by the number of outcomes in the sample space

## Roll two 6-sided dice

1. $$P$$(the sum is 5)
2. $$P$$(the rolls are the same)
3. $$P$$(the sum is even)