Standard Deviation Binomial Dist: n=50, p=0.3, Prob (x > 13 & 13 < x < 17)

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In summary, the formula for standard deviation in a binomial distribution is &#8730;(n * p * (1-p)). Standard deviation is related to variance as its square root, and it is important in interpreting a binomial distribution as it measures the spread of data and identifies outliers. To find probabilities in a binomial distribution, standard deviation can be used with the cumulative probability formula or by subtracting binomial distribution probabilities. Changing the values of n and p in a binomial distribution affects the standard deviation, with larger values resulting in a larger standard deviation and smaller values resulting in a smaller standard deviation.
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jim1174
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find the standard deviation for the binomial distribution which has stated values of n=50 and p=0.3. use normal distribution to approximate the binomial distribution and find probability of (a) x> 13 and (b) 13<x 17.
 
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? Any reason why we should?

1) This looks like homework, not something you are just interested in.

2) Everything you ask here can be done by using simple formulas. What are they?

Show what you have done yourself so we will know where you need help.

I am moving this to the homework section.
 
  • #3


I would first clarify that the given content is referring to a binomial distribution, which is a discrete probability distribution that describes the number of successes in a fixed number of independent trials, each with a constant probability of success. In this case, the stated values of n=50 and p=0.3 indicate that there are 50 trials with a probability of success of 0.3 for each trial.

To find the standard deviation for this binomial distribution, we can use the formula σ = √(np(1-p)), where σ represents the standard deviation, n represents the number of trials, and p represents the probability of success for each trial. Plugging in the given values, we get σ = √(50*0.3*0.7) ≈ 3.85.

Next, using the normal distribution to approximate the binomial distribution, we can find the probability of (a) x> 13 and (b) 13<x<17. To do this, we can use the formula P(x) = Φ((x-μ)/σ), where Φ is the cumulative distribution function of the standard normal distribution, μ is the mean (np), and σ is the standard deviation (√np(1-p)).

For (a) x>13, we would calculate P(x>13) = 1 - P(x≤13) = 1 - Φ((13-15)/3.85) ≈ 1 - Φ(-0.52) ≈ 1 - 0.3015 ≈ 0.6985.

For (b) 13<x<17, we would calculate P(13<x<17) = P(x<17) - P(x≤13) = Φ((17-15)/3.85) - Φ((13-15)/3.85) ≈ Φ(0.52) - Φ(-0.52) ≈ 0.3015 - 0.3015 ≈ 0.

In conclusion, the standard deviation for the given binomial distribution is approximately 3.85, and the probability of (a) x>13 is 0.6985 and (b) 13<x<17 is 0.
 

1. What is the formula for calculating standard deviation for a binomial distribution with n=50 and p=0.3?

The formula for calculating standard deviation for a binomial distribution is: √(n * p * (1-p)), where n is the number of trials and p is the probability of success.

2. How is standard deviation related to variance in a binomial distribution?

Standard deviation is the square root of the variance, which is the average of the squared differences between each data point and the mean. In a binomial distribution, the variance is equal to n * p * (1-p).

3. Why is standard deviation important in interpreting a binomial distribution?

Standard deviation measures the spread of data around the mean, so it is important in understanding the variability of the data in a binomial distribution. It also helps identify outliers and determine the probability of outcomes falling within a certain range.

4. How can I use standard deviation to find the probability of getting more than 13 or between 13 and 17 successes in a binomial distribution with n=50 and p=0.3?

To find the probability of getting more than 13 successes, you would use the formula for the cumulative probability of a binomial distribution: P(x > 13) = 1 - binom.dist(13, 50, 0.3, TRUE). To find the probability of getting between 13 and 17 successes, you would use the formula: P(13 < x < 17) = binom.dist(17, 50, 0.3, TRUE) - binom.dist(13, 50, 0.3, TRUE).

5. How does changing the values of n and p in a binomial distribution affect the standard deviation?

Increasing the value of n while keeping p constant will result in a larger standard deviation, as there are more trials and therefore more potential for variability. Similarly, increasing the value of p while keeping n constant will also result in a larger standard deviation, as there is a higher probability of success in each trial. Conversely, decreasing n or p will result in a smaller standard deviation.

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