Conditional Probabilities Statistical Independence. Week 6 (1) - презентация, доклад, проект скачать

Нажмите для полного просмотра!

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №1

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №2

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №3

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №4

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №5

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №6

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №7

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №8

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №9

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №10

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №11

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №12

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №13

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №14

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №15

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №16

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №17

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №18

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №19

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №20

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №21

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №22

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №23

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №24

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №25

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №26

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №27

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №28

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №29

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №30

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №31

Conditional Probabilities Statistical Independence. Week 6 (1), слайд №32

Содержание ▲

Вы можете ознакомиться и скачать презентацию на тему Conditional Probabilities Statistical Independence. Week 6 (1). Доклад-сообщение содержит 32 слайдов. Презентации для любого класса можно скачать бесплатно. Если материал и наш сайт презентаций Mypresentation Вам понравились – поделитесь им с друзьями с помощью социальных кнопок и добавьте в закладки в своем браузере.

Слайды и текст этой презентации

Слайд 1

Описание слайда:

BBA182 Applied Statistics Week 6 (1) Conditional Probabilities Statistical Independence Dr Susanne Hansen Saral Email: susanne.saral@okan.edu.tr

Слайд 2

Описание слайда:

Interpreting probability No matter what method is used to assign probabilities, we interpret the probability, using the relative frequency approach for an infinite number of trails. The probability is only an estimate (Turkish: tahmin), because the relative frequency approach defines probability as the “long-run” relative frequency. The larger the number of observations the better the estimate will become. Ex.: Tossing a coin Head and tail will only occur 50 % in the long run Computer simulations

Слайд 3

Описание слайда:

Слайд 4

Описание слайда:

Слайд 5

Описание слайда:

Definition of marginal probability Represent the totals found in the margins of a contingency table: Marginal probabilities

Слайд 6

Описание слайда:

Definition of joint events (AB) Two events occur together : Joint probabilities

Слайд 7

Описание слайда:

The following contingency table shows opinion about global warming among U.S. adults, broken down by political party affiliation.

Слайд 8

Описание слайда:

A) What is the probability that a U.S. adult selected at random believes that global warming is a serious problem? B) What type of probability did you find in part A? (marginal or joint probability) C) What is the probability that a U.S. adult selected at random is a Republican and believes that global warming is a serious issue? D) What type of probability did you find in part C? (marginal or joint probability)

Слайд 9

Описание слайда:

A) What is the probability that a U.S. adult selected at random believes that global warming is a serious problem? = = 63 % B) What type of probability did you find in part A? (marginal or joint probability) Marginal probability C) What is the probability that a U.S. adult selected at random is a Republican and believes that global warming is a serious issue? = = 18 % D) What type of probability did you find in part C? Joint probability

Слайд 10

Описание слайда:

Conditional Probability What if we were given the information that the selected person is a republican, instead of U.S. adult? Would that change the probability that the selected person’s opinion about global warming is a nonissue?

Слайд 11

Описание слайда:

Conditional Probability

Слайд 12

Описание слайда:

Conditional Probability When we restrict our focus to republicans, we look only at the republican’s row of the table, Which gives the conditional probability of opinion on Global warming “given” the person is republican.

Слайд 13

Описание слайда:

Conditional Probability Of the 500 republicans, 290 of them say that global warming is not an issue. We write the probability that a random selected persons believes that global warming is not an issue “given” the person is republican: P(nonissuerepublican) = = 0.58 or 58 %

Слайд 14

Описание слайда:

Conditional Probability If we now focus on democratic instead. Of the 500 democratic people only 85 say that global warming is a nonissue: We write the probability that a random selected persons believes that global warming is not an issue “given” the person is democratic: P(nonissuedemocratic) = = 0.17 or 17 %

Слайд 15

Описание слайда:

Conditional Probability If we focus on “serious concern”: Of the 755 people who say that global warming is a serious concern 415 are democratic We write the probability that a random selected person is democratic “given” the person is says global warming is a serious concern: P(democratic serious concern) = = 0.549 or 55%

Слайд 16

Описание слайда:

Conditional Probability P(nonissue |republican) = = = .58

Слайд 17

Описание слайда:

Conditional Probability A conditional probability is the probability of one event, given that another event has already occurred:

Слайд 18

Описание слайда:

Conditional Probability - Example What is the probability that a car has a CD player, given that it has AC ? i.e., we want to find P(CD | AC)

Слайд 19

Описание слайда:

Conditional Probability Example

Слайд 20

Описание слайда:

Conditional Probability Example

Слайд 21

Описание слайда:

Conditional Probability – manufacturing example 1. What is the probability that the computer chip was delivered by Manufacturer B given it was defective? P(B|D) = 2. What is the probability that the chip was satisfactory given it was delivered by Manufacturer B? P(S|B) =

Слайд 22

Описание слайда:

Conditional Probability - example 1. What is the probability that the computer chip was delivered by Manufacturer B given it was defective? P(B|D) = = = 0.625 or 62.5 % 2. What is the probability that the chip was satisfactory given it was delivered by manufacturer B? P(S|B) = = = 0.9498 or 94.98 %

Слайд 23

Описание слайда:

Conditional Probability - example 1. What is the probability that the computer chip was delivered by Manufacturer A given it was defective? P(A|D) = 2. What is the probability that the chip was satisfactory given it was delivered by manufacturer A? P(S|A) =

Слайд 24

Описание слайда:

Conditional Probability - example 1. What is the probability that the computer chip was delivered by Manufacturer A given it was defective? P(A|D) = = = 0.375 or 37.5 % 2. What is the probability that the chip was satisfactory given it was delivered by manufacturer A? P(S|A) = = = .9800 or 98 %

Слайд 25

Описание слайда:

Class exercises Discrimination in the workplace is illegal and companies that do so are often sued. The female professors at a large university recently sued the university, about the last round of promotions from assistant professor to associate professor: An analysis of the relationship between gender and promotion produced the following probabilities:

Слайд 26

Описание слайда:

Class exercises What is the probability of promotion given female assistant professors ? What is the probability of promotion given male assistant professors? Is it reasonable to accuse the university of gender difference?

Слайд 27

Описание слайда:

Class exercises (continued) Solution: P(promoted│female) = = = .2 or 20% P(promoted│male) = = or 20 % There is no reason to accuse the university for discrimination

Слайд 28

Описание слайда:

Statistical Independence Two events are statistically independent if and only if: Events A and B are independent when the probability of one event is not affected by the other event If A and B are independent, then

Слайд 29

Описание слайда:

Statistical independence From our previous example about global warming: Is saying: Global warming is not an issue, independent of the political party the person is a member of? We need to check: If the P(nonissue|republican) = P(nonissue) ? P(nonissue|republican) = = = .57 P(nonissue) = .37 P(nonissue|republican) P(nonissue), therefore the events are not independent

Слайд 30

Описание слайда:

Statistical Independence Car example

Слайд 31

Описание слайда:

Class exercise Independent-dependent events Determine whether the event A3 and B2 are independent or dependent events. P(A3|B2) = P(A3)? Determine whether the events B1 and A1 are independent or dependent events. P(A1|B1) =P(A1)?

Слайд 32

Описание слайда:

Solution: P = = 0.25 P(A3) = 0.2 P P(A3) They are dependent events P(A1 = = = 0.5 P(A1) = .4 P(A1 P(A1) They are dependent event In general, if one combination of events is independent (or dependent) then the other combinations in the table are independent (or dependent).