Chapter 17 & 18 Notes
Chapter 17 & 18 Notes STAT 110 - 002
Popular in Introduction to Statistical Reasoning
STAT 110 - 002
verified elite notetaker
Popular in Statistics
This 4 page Class Notes was uploaded by Kara Lyles on Saturday March 26, 2016. The Class Notes belongs to STAT 110 - 002 at University of South Carolina taught by Gail Ward-Besser (P) in Spring 2016. Since its upload, it has received 93 views. For similar materials see Introduction to Statistical Reasoning in Statistics at University of South Carolina.
Reviews for Chapter 17 & 18 Notes
Report this Material
What is Karma?
Karma is the currency of StudySoup.
Date Created: 03/26/16
Chapter 18 Definitions Probability model- all possible outcomes Ex. If you toss a coin 3 times. What is the chance it lands on tails? (2^3=8) ANSWER: 8 Sample space - unique outcome Ex. When tossing a coin a unique outcome would be either heads or tails. Sample space= head (H) Tails (T) Event - collection of outcome Probability Rules Rule 1 : probability must be a number between 0 and 1 Rule 2: all possible outcome must = 1 *if it passes both rules 1&2 it’s legitimate Rule 3 AKA compliment rule: if the question ask what is the probability that the event doesn’t occur? Use this Formula: 1 - probability the event WILL Occur Probability = numerical (has to be a number) Ex. Probability of dog losing the race is .40, what is the probability of it winning? ANSWER: . 70 Complement = Opposite (think opposite) Ex. What is the compliment of the dog losing? ANSWER: The dog winning Rule 4: Union Rule, think united so there is addition. Probabilities must be disjoint. Formula: P (A or B) = P (A) +P (B) *There may be an instance where given 2 disjoint probabilities and then a probability of both occurring. If asked the probability of both occurring use this formula: P (A) + P (B) - P (A&B) Rule 5 Multiplication rule: If events are INDPENDENT of each other multiply. Sampling distribution- “Tells values a STATISTIC takes in repeated samples from the same population” **** Central Limit Theorem-the sampling distribution for the statistic is normally distributed when you take many, many samples of sufficiently large sample size (WILL BE ON TEST) Chapter 17 Definitions Random- individual outcomes uncertain but reaches random distribution over a lot of repetitions. Probability - # between 0&1 which describe the proportion of times an outcome will occur IF Probability =0 outcome never occurs IF probability = 1 outcome will occur every time IF probably = 1/2 outcome eventually happens half the time Types of Probabilities Empirical (experimental): experiment must take place YOU had to do something Theoretical: assumption Based on set theories Personal probability : personal judgement (you must believe it) Probability of an outcome= Number of ways for an outcome to occur / total number of outcomes. Law of large numbers: if numerical outcomes is repeated independently many times. * The mean of the observed outcomes will approach the expected value. Ex. Chance of getting heads or tails is 1/2. The more times you flip the coin the closer it will get to its expected value which is 1/2 Large of law numbers is about means and proportion. When speaking of odd assign A to the first probability and Assign B to the second one. If odds are for you use formula: A/ (A+B) If odds are against you use formula: B/ (A+B) If only given one probability use formula: O/ (1+O)