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I am Basan Shrestha from Kathmandu, Nepal. I use the term 'BASAN' as 'Balancing Actions for Sustainable Agriculture and Natural Resources'. I am a Design, Monitoring & Evaluation professional. I hold 1) MSc in Regional and Rural Development Planning, Asian Institute of Technology, Thailand, 2002; 2) MSc in Statistics, Tribhuvan University (TU), Kathmandu, Nepal, 1995; and 3) MA in Sociology, TU, 1997. I have more than 10 years of professional experience in socio-economic research, monitoring and documentation on agricultural and natural resource management. I had worked in Lumle Agricultural Research Centre, western Nepal from Nov. 1997 to Dec. 2000; CARE Nepal, mid-western Nepal from Mar. 2003 to June 2006 and WTLCP in far-western Nepal from June 2006 to Jan. 2011, Training Institute for Technical Instruction (TITI) from July to Sep 2011, UN Women Nepal from Sep to Dec 2011 and Mercy Corps Nepal from 24 Jan 2012 to 14 August 2016 and CAMRIS International in Nepal commencing 1 February 2017. I have published articles to my credit.

Tuesday, May 14, 2019

Multiplication Rule of Dependent Events, Statistical Note 39

If two cards are drawn without replacement from a deck of cards, what is the joint probability that both cards are red?
The multiplication rule of probability of two dependent events is the product of the probability of first independent marginal event and the conditional probability of second dependent marginal event. Same applies to the joint probability of multiple dependent events.
Symbolically, let A be an independent event and B be a dependent event, the joint probability that both events and A and B occur is stated as:
P(A and B) = P(A)*P (B/A), where P(A) is the probability of an independent event A and P(B/A) is the conditional probability of a dependent event B given the occurrence of an independent event A.
The events are said to be dependent events if the occurrence of the first event affects the probability of the second and following events. In this example, drawing of a red card in the first event and not replacing back that card to the deck of cards before second draw of a card affects the second draw of a card. This applies to multiple draws of cards without replacement from a deck of cards.
Let R1 be an independent event of drawing a red card in the first draw of a card.  There are 26 red cards in a deck of cards. The marginal probability of R1, P(R1) is 26 divided by 52, 0.5. Let R2 be a dependent event of drawing a red card from the deck of cards in which the first drawn card is not replaced back.  There are 25 red cards left in the deck of 51 cards, as the first drawn cards is red which is not replaced back in the deck. Thus, the conditional probability of R2 given R1 in the first draw, P(R2/R1) is 25 divided by 51, 0.4902.
Now, applying the multiplication rule of dependent events, the joint probability that red cards are drawn in both draws without replacement is the product of P(R1) in the first draw and the P(R2) in the second draw.
Symbolically, P(R1 and R2) = P(R1)*P (R2/R1)=26/52 *25/51 =0.2450
The total number of outcomes in two draws of cards without replacement from a deck of cards and their probabilities are shown using a tree diagram below:









Figure 1: Marginal probabilities of first draws and conditional probabilities of second draws given the first draws of cards without replacement and joint probabilities of possible outcomes

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