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Business Stats notes Chapter 5

by: Hannah Musser

Business Stats notes Chapter 5 ST 260

Marketplace > University of Alabama - Tuscaloosa > Statistics > ST 260 > Business Stats notes Chapter 5
Hannah Musser
GPA 3.5

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This is part 1 of chapter 5. I'll upload the second part on friday morning after the lecture. These notes include examples that are broken down. You won't find these examples on the power point.
Statistical Data Analysis
Cali Davis
Class Notes
Statistics 260
25 ?




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This 3 page Class Notes was uploaded by Hannah Musser on Wednesday February 10, 2016. The Class Notes belongs to ST 260 at University of Alabama - Tuscaloosa taught by Cali Davis in Winter 2016. Since its upload, it has received 131 views. For similar materials see Statistical Data Analysis in Statistics at University of Alabama - Tuscaloosa.

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Date Created: 02/10/16
ST 260 Chapter 5 Note. Part 1 – 2/10/14 Prof. Cali Davis Quick Recall:  ­ Quantitative Variables: differences that have meaning to them, such as age, income,  height, and weight.  ­ Qualitative Variable (OR categorical): putting people or things into classifications. Such  as: gender, race, occupation, country, or political affliction.  Statistics can be described as “the science of decision­making in the face of uncertainty”  (An educated guess) So how do we measure uncertainty?  ­ Using probability: A numerical value or measure of the LIKLIHOOD that a certain  outcome or event occurs.  P(A)= probability of eventA ­ Probability requirements for discrete variables: 0 less than or equal to P(A), which is also less than or equal to 1 So P(A) is between 0 and 1 The way we look at what 0 is and what 1 is:  P(A) = 0 impossible event  P(A) = 1 certain event **Sum of the probabilities of all possible outcomes must equal one (1)** Example: if the probability that the broncos win the super bowl is half  (50%), and the probability that the panthers win the super bowl is half (50%), than the  sum of the probabilities equals 1 (100%).  ½ + ½ = 1 Probability can be conditioned under certain circumstances Conditioned Probability: The chance one event happens, given that another event will  occur. Example: if the broncos when the super bowl, the bars will probably sell more alcohol. Example : if the panthers win the super bowl, the broncos’ fans will probability start a riot. P(A | B) =P(A and B)/ P(B) = All outcomes belonging to BOTH A AND B  Divided By Those outcomes in the restricted group, B  Example Problem: (Cali Davis lecture) Credit Card Manager  ­ New credit test to determine credit worthiness. Credit test checked against 500 previous  customers. CREDIT TEST A Credit History:  Passed (P) Failed (F) 350 50 20 80 370 130 Good (G) ­1  row Default (D) ­2  row 1  row = total 400      row = total 100 Total both rows = 500 What is the probability of a customer defaulting? ­ 80 people failed and defaulted.  What is the probability of a customer defaulting given that he fails test A? ­ General rules P(A and B)  = P(A)  P(B|A)  = P(B)  P(A|B)  P(A or B) = P(A) + P(B) ‐ P(A and B) Look at the part that overlaps  Does knowledge from test A help you make a better decision?  P(D)= .20 P(D/F)= .62  Do you want to know the test A results before you give the loan?  “Credit test A results” and “defaulting” are dependent variables.


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