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Vsevolod [243]
3 years ago
15

Which of these is NOT a characteristic of a binomial experiment? A. What happens on one trial affects the probability on the nex

t: they are dependent events. B. Each trial results in one of two possible outcomes: success or failure. C. The coefficient of the binomial term can be determined using Pascal’s triangle. D. The probability of success () on a single trial is the same for all trials.
Mathematics
1 answer:
nignag [31]3 years ago
6 0

Answer:

A. What happens on one trial affects the probability on the next: they are dependent events.

Step-by-step explanation:

Below are some important characteristic of a binomial experiment:-

  • A binomial experiment has n trials.
  • Each trials has two possible outcomes. Success or failure.
  • The probability of success is same in very trail.
  • The event is independent event. In other words, the probability of one event doesn't effect the other.
  • The coefficient of the binomial term can be determined using Pascal’s triangle

Basis these characteristics, only the first option is not a properties of a binomial experiment. In case of binomial experiment, the event is independent event.

Hence, option A is correct.

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2 years ago
I need help with this!And also can they play 6 levels during their free trial?
djverab [1.8K]

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How do i find the value of a variable?
photoshop1234 [79]

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2 years ago
Need help
aleksandr82 [10.1K]

Using the normal distribution, the probabilities are given as follows:

a. 0.4602 = 46.02%.

b. 0.281 = 28.1%.

<h3>Normal Probability Distribution</h3>

The z-score of a measure X of a normally distributed variable with mean \mu and standard deviation \sigma is given by:

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

  • The z-score measures how many standard deviations the measure is above or below the mean.
  • Looking at the z-score table, the p-value associated with this z-score is found, which is the percentile of X.
  • By the Central Limit Theorem, the sampling distribution of sample means of size n has standard deviation s = \frac{\sigma}{\sqrt{n}}.

The parameters are given as follows:

\mu = 959, \sigma = 263, n = 37, s = \frac{263}{\sqrt{37}} = 43.24

Item a:

The probability is <u>one subtracted by the p-value of Z when X = 984</u>, hence:

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

Z = \frac{984 - 959}{263}

Z = 0.1

Z = 0.1 has a p-value of 0.5398.

1 - 0.5398 = 0.4602.

Item b:

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

By the Central Limit Theorem:

Z = \frac{X - \mu}{s}

Z = \frac{984 - 959}{43.24}

Z = 0.58

Z = 0.58 has a p-value of 0.7190.

1 - 0.719 = 0.281.

More can be learned about the normal distribution at brainly.com/question/4079902

#SPJ1

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Answer:

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Step-by-step explanation:

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2 years ago
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