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week 6 BNAD 276 notes

by: madelinef

week 6 BNAD 276 notes BNAD 276 001

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week 6 BNAD 276 notes
Statistic Inference in Management
Dr. Suzanne Delaney
Class Notes
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This 2 page Class Notes was uploaded by madelinef on Saturday October 1, 2016. The Class Notes belongs to BNAD 276 001 at University of Arizona taught by Dr. Suzanne Delaney in Fall 2016. Since its upload, it has received 4 views.


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Date Created: 10/01/16
Week 6 BNAD 276  Z score o 100% under curve (0.1) o 50% on half of it (0.5)  Probability  Empirical probability- relative frequency approach o Number of observed outcomes/number of observations o Ex: Eller admissions, rotten apples  Classical probability- a priori probability based on logic rather than on data or experience. All options are equally likely o Deductive rather than inductive o Ex; coin toss, dice roll  Subjective probability- based on someone’s personal judgement (usually an expert) and used when empirical or classic are not available o Ex; there is a 5% change a and b will merge. I am 90% sure I can jump over than puddle  Compliment is the probability of not A. o P(A)A’=P(A’) o Ex: if there is a 5% check you get A there is 95% chance you do not get A  Mutually exclusive- if the occurrence of any one of them implies the non-occurrence of the remaining characteristic o Cannot occur at the same time. Cant logically be true. o Ex: can’t be male and female, can’t have an A and a B in the same class as a final grade  Collectively exhausted- if the union is the entire sample space  Union- probability of A or B. P (A U B)  Intersection- probability of A and B. P (A n B) o Issue: things in both groups get counted twice  Conditional probability- probability that A has occurred given that B has occurred. PAlB)= P(A n B)/P(B) o Ex: population 16-21 not in college.  Unemployed= 13.5%-->0.1350  Did not graduate90//05%= 0.2905  If 2 events are mutually exclusive their intersecting is a null set and we can use a special law of addition  Why do we conduct research? o 1. To explore potential phenomena- explore if a phenomenon is present with a fresh take. Generate new ideas and discover relationships o 2. To describe a phenomena- build a vocabulary of constructs and make distinctions, cluster characteristics into related characteristics o 3. To explain and model phenomena- explanation to find cause and effect relationships, propose mechanisms that determine outcomes, show how o 4. To predict future behavior- what characteristics likely to result in x, explanations help with predictions but being able to predict does not equal being able to explain o 5. To influence behavior- how can we use what we know about human behavior to affect how people around us react and behave and do what we want them to do  evaluating investments- the standard deviation refers to the volatility or risk of the investment. o More risklarger standard deviation o The numerator is the difference our investment is from a lowest risk type of investment  Sharpe ratio- also called reward to variability ratio. Formula is o Mean-risk free mean/ standard deviation. o Parallels the same formula as z score!


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