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nydimaria [60]
2 years ago
14

the area of the triangle below is 1/4 square meters. what is the length of the base. express your answer in simplest form

Mathematics
1 answer:
Alexeev081 [22]2 years ago
5 0

Answer:

4/5

Step-by-step explanation:

<u>Given</u>,

Area of the triangle = 1/4 square meters

From the diagram,

Height = 2/5 m

<u>To find</u> : Length of the base

<u>Formula</u> : -

A = bh/2

Here,

A denotes Area

b denotes Base

h denotes Height

A = 1/4

h = 2/5

A = bh/2

Cross multiply,

A * 2 = bh

2A = bh

2 * (1/4) = b * (2/5)

(1 * 2)/4 = (b * 2)/5

2/4 = 2b/5

1/2 = 2b/5

Cross multiply,

1 * 5 = 2 * 2b

5 = 4b

b = 4/5 meters

Hence,

The length of the base is 4/5 meters.

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To calculate the total amount you'll pay add $34.40 to $860 to get $894.40.

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4 years ago
U= ab/k, for a <br> Solve form A
Andre45 [30]
  • Answer:

<em>a = uk/b</em>

  • Step-by-step explanation:

<em>u = ab/k</em>

<em>uk = ab</em>

<em>a = uk/b</em>

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3 years ago
The mean height of women in a country (ages 20-29) is 64 4 inches A random sample of 50 women in this age group is selected What
Simora [160]

Answer:

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

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 establishes 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.

Mean of 64.4 inches, standard deviation of 2.91

This means that \mu = 64.4, \sigma = 2.91

Sample of 50 women

This means that n = 50, s = \frac{2.91}{\sqrt{50}}

What is the probability that the mean height for the sample is greater than 65 inches?

This is 1 subtracted by the p-value of Z when X = 65. So

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

By the Central Limit Theorem

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

Z = \frac{65 - 64.4}{\frac{2.91}{\sqrt{50}}}

Z = 1.46

Z = 1.46 has a p-value of 0.9279

1 - 0.9279 = 0.0721

0.0721 = 7.21% probability that the mean height for the sample is greater than 65 inches.

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