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4 years ago

A couple decided to have 4 children.

1 answer:

7 0

See below the theee of possibilities:

BBBB
BBBG
BBGB
BBGG
BGBB
BGBG
BGGB
BGGG
GBBB
GBBG
GBGB
GBGG
GGBB
GGBG
GGGB
GGGG

There are 16 differents possibilities.
In 11 of them have at least 2 boys

So probability is 11/16

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I need an explanation, I don't understand them

Anettt [7]

The value of the fractions will be:

1. 8 13/20

2. 2 4/5

3. 5/6

<h3>How to explain the fraction?</h3>

1. 6 1/4 + 2 2/5

LCM of 20

6 1/4 + 2 2/5.

6 5/20 + 2 8/20

= 8 13/20

2. 1 1/5 × 2 1/3

= 6/5 × 7/3

= 42/15

= 14/5

= 2 4/5

3. 3 1/3 - 2 1/2

= 3 2/6 - 2 3/6.

= 5/6

Learn more about fractions on:

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5 0

2 years ago

Which statements describe lorelei’s solution? check all that apply. her work is correct. her answer is correct. in step 1, the s

MArishka [77]

12! divided by 10! is not equivalent to 6! divided by 5!. Then the correct statement is 3.

<h3>What is the combination?</h3>

Combinations are the way of selecting objects or elements from a group of objects or collections, in such a way the order of the objects does not matter.

The statements are given below.

Statement 1 - The subtraction cannot be completed before the factorial of each number is calculated. This is the incorrect statement.

Statement 1 - 12! divided by 10! is not equivalent to 6! divided by 5!. This is the correct statement.

Statement 3 - The dividing out of common factors was performed incorrectly. There are sixty-six ways to choose ten items from twelve. This is the incorrect statement.

More about the combination link is given below.

brainly.com/question/11732255

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8 0

2 years ago

Consider the probability that exactly 90 out of 148 students will pass their college placement exams. Assume the probability tha

Pepsi [2]

Answer:

0.0491 = 4.91% probability that exactly 90 out of 148 students will pass their college placement exams.

Step-by-step explanation:

Binomial probability distribution

Probability of exactly x successes on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

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

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

Assume the probability that a given student will pass their college placement exam is 64%.

This means that $p = 0.64$

Sample of 148 students:

This means that $n = 148$

Mean and standard deviation:

$\mu = E(X) = np = 148(0.64) = 94.72$

$\sigma = \sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{148*0.64*0.36} = 5.84$

Consider the probability that exactly 90 out of 148 students will pass their college placement exams.

Due to continuity correction, 90 corresponds to values between 90 - 0.5 = 89.5 and 90 + 0.5 = 90.5, which means that this probability is the p-value of Z when X = 90.5 subtracted by the p-value of Z when X = 89.5.

X = 90.5

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

$Z = \frac{90.5 - 94.72}{5.84}$