Statistics - Binomial Probability question

• theIBnerd
In summary, the conversation is about finding the probability of defective computer chips in a batch of 1000, using the normal approximation to the binomial probability distribution with a continuity correction. The person asking the question has provided their answer using a calculator, but the textbook offers a different answer. It is revealed that the person may not have used the continuity correction, as their teacher did not mention it. They will work on correcting their solution.
theIBnerd
Hi. i keep finding a different answer than what textbook offers. is my answer correct?

question: the quality control department of a company making computer chips knows that 2% of the chips arw defective. use the nurmal approximation to the binomial probability distribution, with a continuity correction, to find the probability that, in a batch containing 1000 chips, between 20 and 30 chips (inclusive) are defective.

using TI 84+
but the textbook says the answer is: 0.5349

is there anything wrong with my solution? what do you think is the real answer?

thank you

You aren't using the continuity correction - you aren't even using the normal approximation.

You aren't using the continuity correction - you aren't even using the normal approximation.

oh. i will work on that.

turns out my teacher has not said a single word on continuity correction and normal approximation. so i just assumed i could solve it using commulative thing.

1. What is binomial probability?

Binomial probability is a statistical concept that deals with the likelihood of a particular outcome in a series of independent trials. It is used to calculate the probability of obtaining a certain number of successes in a fixed number of trials, with only two possible outcomes for each trial - success or failure.

2. How is binomial probability calculated?

The formula for calculating binomial probability is P(x) = nCx * p^x * (1-p)^(n-x), where n is the number of trials, x is the number of successes, and p is the probability of success for each trial. "nCx" represents the combination of n trials taken x at a time.

3. Can binomial probability be used for continuous data?

No, binomial probability is specifically used for discrete data, where there are only two possible outcomes for each trial. For continuous data, other probability distributions such as the normal distribution or Poisson distribution may be more appropriate.

4. What is the difference between binomial probability and binomial distribution?

Binomial probability refers to the likelihood of a specific outcome in a set of trials, while binomial distribution refers to the pattern of all possible outcomes in a set of trials. In other words, binomial probability is a single value, while binomial distribution is a range of values.

5. How is binomial probability used in real life?

Binomial probability is used in a variety of fields, including finance, medicine, and market research. For example, it can be used to calculate the probability of a new medication being effective in a certain percentage of patients, or the likelihood of a certain stock price increasing after a certain number of days.

• Calculus and Beyond Homework Help
Replies
2
Views
1K
• Calculus and Beyond Homework Help
Replies
3
Views
2K
• Calculus and Beyond Homework Help
Replies
30
Views
4K
• Calculus and Beyond Homework Help
Replies
1
Views
3K
• Calculus and Beyond Homework Help
Replies
2
Views
4K
• Calculus and Beyond Homework Help
Replies
2
Views
1K
• Calculus and Beyond Homework Help
Replies
4
Views
1K
• Calculus and Beyond Homework Help
Replies
5
Views
2K
• Precalculus Mathematics Homework Help
Replies
2
Views
2K
• Calculus and Beyond Homework Help
Replies
19
Views
6K