What is a binomial distribution in short and long terms

Mathematics

2 answers:

Gemiola [76]3 years ago

8 0

Answer:

Binomial distribution summarizes the number of trials, or observations when each trial has the same probability of attaining one particular value. The binomial distribution determines the probability of observing a specified number of successful outcomes in a specified number of trials.

Mama L [17]3 years ago

8 0

Answer:

The binomial is a type of distribution that has two possible outcomes (the prefix “bi” means two, or twice). For example, a coin toss has only two possible outcomes: heads or tails and taking a test could have two possible outcomes: pass or fail. A Binomial Distribution shows either (S)uccess or (F)ailure.

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Irina-Kira [14]

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4 years ago

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<img src="https://tex.z-dn.net/?f=e%20%3D%20mc%20%7B2%7D" id="TexFormula1" title="e = mc {2}" alt="e = mc {2}" align="absmiddle"

serg [7]

Answer:

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Hope this helped

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3 years ago

The volume v of a sphere with radius r is given by formula v=4/3 . if radius of a spherical rubber ball is 1 1\4 inches , what i

Aliun [14]

Actually, the correct volume formula is:
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3 years ago

g Annual starting salaries in a certain region of the U. S. for college graduates with an engineering major are normally distrib

algol13

Answer:

The probability that the sample mean would be at least $39000 is of 0.8665 = 86.65%.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .