Understanding Sample Proportions and the Binomial Distribution

In summary, a probability distribution is a mathematical function that describes the likelihood of a random variable taking on a certain value or range of values. There are several types of probability distributions, including the normal distribution, binomial distribution, Poisson distribution, and exponential distribution, and each type is used to model different types of data or events. A probability distribution can be represented through a graph, table, or mathematical formula, with the most common representation being a graph. There is a difference between a discrete and a continuous probability distribution, with the former being used for data with specific values and the latter for data with a range of values. Probability distribution is used in various fields and in everyday life to make predictions, analyze data, and aid in decision making
  • #1
smallso
1
0
Hi,

I am doing a past paper but I am kinda stuck on one of the questions.

These are the answers I have:
2a. 225/260 = 0.8654
2b. 32/260 * 4/32 = 0.01407
2c. 32/260 * 28/32 + 228/260 * 221/228 = 0.9577

Then for 2d, I have no idea what to do. Am i suppose to draw one of those probability distribution table? And what does it mean sample proportion of accurate ZikaCheck result?

Thank you very much.
 

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  • #2
Hi smallso,

Have you covered the binomial distribution? Usually when we talk about proportions that are related to two outcomes this involves this distribution. Does that sound familiar?
 

FAQ: Understanding Sample Proportions and the Binomial Distribution

1. What is a probability distribution?

A probability distribution is a mathematical function that describes the likelihood of a random variable taking on a certain value or range of values. It shows all the possible outcomes of an event and their associated probabilities.

2. What are the types of probability distributions?

There are several types of probability distributions, including the normal distribution, binomial distribution, Poisson distribution, and exponential distribution. Each type is used to model different types of data or events.

3. How is a probability distribution represented?

A probability distribution can be represented in various ways, such as a graph, a table, or a mathematical formula. The most common way to represent a probability distribution is through a graph, which shows the relationship between the possible outcomes and their associated probabilities.

4. What is the difference between a discrete and a continuous probability distribution?

A discrete probability distribution is used for data that can only take on specific values, such as the number of students in a class. A continuous probability distribution is used for data that can take on any value within a certain range, such as the height of a person.

5. How is probability distribution used in real life?

Probability distribution is used in various fields, such as statistics, economics, and engineering, to make predictions and analyze data. It is also used in gambling and insurance to calculate risks and potential outcomes. In everyday life, probability distribution can help in decision making, such as choosing the best route to take based on the likelihood of traffic or weather conditions.

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