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algol13
3 years ago
14

True or False

Mathematics
1 answer:
Rama09 [41]3 years ago
7 0

Answer:

True

Step-by-step explanation:

Permutation is act of arranging members of a set while combination is selection of the items from collection.

The number of permutation of r object out of n is:

^nP_r=\frac {n!}{(n-r)!}

The number of combinations of r object out of n is:

^nC_r=\frac {n!}{(n-r)!\times r!}

Or,  

^nC_r=\frac {^nP_r}{r!}

So, number of the permutations of r objects out of n is greater than number of the combinations of r objects out of n.

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PLEASE HELP ASAP GEOMETRY 20 PTS REAL ANSWERS ONLY
kodGreya [7K]

Answer:

Step-by-step explanation:

Use the Law of Cosines to find the measure of angle A from the lengths of the sides.

A = arccos[(b²+c²-a²)/(2bc)] ≅ 29.9°

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2 years ago
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s344n2d4d5 [400]

Answer:

64°

Step-by-step explanation:

First, we have to find the angle situated in R, the addition of all angles in a triangle is 180° so that means:

x + 68 + 48 = 180

x = 180-116 = 64°

Now, remember that this angle (64°) is the same as this one = ?, thanks to one property.

So basically, that angle has the same value as that one.

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8 0
3 years ago
Consider the question of whether the home team wins more than half of its games in the National Basketball Association. Suppose
spayn [35]

Answer:

0.0037 = 0.37% probability that the home team would win 65% or more of its games in a simple random sample of 80 games

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 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.

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}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean \mu = p and standard deviation s = \sqrt{\frac{p(1-p)}{n}}

The home team therefore wins 50% of its games

This means that p = 0.5

Determine the probability that the home team would win 65% or more of its games in a simple random sample of 80 games

Sample of 80 means that n = 80 and, by the Central Limit Theorem:

\mu = p = 0.65

s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.5*0.5}{80}} = 0.0559

This probability is 1 subtracted by the pvalue of Z when X = 0.65. So

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

By the Central Limit Theorem

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

Z = \frac{0.65 - 0.5}{0.0559}

Z = 2.68

Z = 2.68 has a pvalue of 0.9963

1 - 0.9963 = 0.0037

0.0037 = 0.37% probability that the home team would win 65% or more of its games in a simple random sample of 80 games

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2 years ago
Simplify the following
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