Statistics and Discrete distributions

In summary, the probabilities of blood types O, A, B and AB are 0.46, 0.39, 0.12, 0.03 respectively. When seeking either type O or B from six random individuals, the probability of at least 2 people having the desired blood type can be calculated using a binomial distribution.
  • #1
amai
3
0

Homework Statement


The probabilities of blood types O, A, B and AB are 0.46, 0.39, 0.12, 0.03 respectively.
If a clinic is seeking either type O or B from six random individuals, what is the probability that at least 2 people have the desired blood type?

Homework Equations





The Attempt at a Solution



I'm not really sure where to start. From the questions, I don't think it's a binomial distribution or a poisson distribution. All i have so far is...

Where X=people with the desired blood type

P(X≥ 2)=1-P(0)-(P(1)

Any suggestions?
 
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  • #2
Since the probability of being O is 0.46 and the probability of being B is 0.12, what is the probability of being either O or B?

What is the probability of not being either O or B, or in other words, what is the probability of being A or AB?
 
  • #3
amai said:

Homework Statement


The probabilities of blood types O, A, B and AB are 0.46, 0.39, 0.12, 0.03 respectively.
If a clinic is seeking either type O or B from six random individuals, what is the probability that at least 2 people have the desired blood type?

Homework Equations





The Attempt at a Solution



I'm not really sure where to start. From the questions, I don't think it's a binomial distribution

You are conducting six independent trials, in which success in a trial is defined as "this person has type O or B blood". That gives you a binomial distribution.
 

1. What is the difference between statistics and discrete distributions?

Statistics is a branch of mathematics that deals with collecting, analyzing, and interpreting data. Discrete distributions, on the other hand, refer to a set of possible outcomes in a statistical experiment that can be counted and are distinct from one another. In simpler terms, statistics is a field of study, while discrete distributions are a type of data analysis tool.

2. What are some examples of discrete distributions?

Some examples of discrete distributions include the binomial distribution, Poisson distribution, and geometric distribution. These distributions are used to model the probability of a specific number of successes or events occurring in a given number of trials or time periods.

3. How are discrete distributions different from continuous distributions?

Discrete distributions only have a finite or countable number of possible outcomes, while continuous distributions have an infinite number of possible outcomes. Discrete distributions also deal with events that can be counted, while continuous distributions deal with events that can take on any value within a range.

4. What is the importance of using discrete distributions in statistics?

Discrete distributions are important in statistics because they allow us to analyze and make predictions about real-world events that have a finite number of possible outcomes. They also provide a way to model and understand the probability of these outcomes occurring.

5. How are discrete distributions used in real-world applications?

Discrete distributions are used in various fields such as finance, biology, and engineering to analyze and make predictions about events with a finite number of possible outcomes. For example, the binomial distribution is used to model the probability of success in a series of trials, while the Poisson distribution is used to model the number of events occurring in a specific time period.

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