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Lady bird [3.3K]
3 years ago
5

In a chest there are some gold coins. Captain takes half the

Mathematics
2 answers:
Julli [10]3 years ago
5 0

Answer:

There were 12 gold coins in the chest at the start.

Step-by-step explanation:

1. Let's review the information given to us to answer the question correctly:

x = Number of gold coins in a chest

1/2x = Number of gold coins taken by the captain

1/4x = Number of gold coins taken by Sally

3 = Number of gold coins left

2. How many coins were in the chest at the start?

Let's write the following equation to solve for x:

1/2x + 1/4x + 3 = x

2x + x + 12 = 4x (Lowest Common Denominator is 4)

4x - 2x - x = 12 (Like terms)

x = 12

There were 12 gold coins in the chest at the start.

Hope this helps :D

Alina [70]3 years ago
3 0

Answer:

7

Step-by-step explanation:

4+3=7

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sineoko [7]

Step-by-step explanation:

5x-17 and 3x-11 are supplementary angles

They add up to 180 degrees

5x-17 + 3x - 11 = 180

8x - 28 = 180

8x= 208

x= 26

3x-11, 90, and 2y + 5 added together equal 180

3x-11 + 90 + 2y + 5 = 180

3(26) - 11 + 2y + 5 = 90

78 - 6 + 2y = 90

72 + 2y = 90

2y = 18

y = 9

I hope this helps!!!

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3 years ago
Slope = 6 , through = (4,13)
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Answer:

y=6x-11

Step-by-step explanation:

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6 0
2 years ago
The mean of a population is 74 and the standard deviation is 15. The shape of the population is unknown. Determine the probabili
Lena [83]

Answer:

a) 0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

b) 0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c) 0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

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}}.

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

The mean of a population is 74 and the standard deviation is 15.

This means that \mu = 74, \sigma = 15

Question a:

Sample of 36 means that n = 36, s = \frac{15}{\sqrt{36}} = 2.5

This probability is 1 subtracted by the pvalue of Z when X = 78. So

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

By the Central Limit Theorem

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

Z = \frac{78 - 74}{2.5}

Z = 1.6

Z = 1.6 has a pvalue of 0.9452

1 - 0.9452 = 0.0548

0.0548 = 5.48% probability of a random sample of size 36 yielding a sample mean of 78 or more.

Question b:

Sample of 150 means that n = 150, s = \frac{15}{\sqrt{150}} = 1.2247

This probability is the pvalue of Z when X = 77 subtracted by the pvalue of Z when X = 71. So

X = 77

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

Z = \frac{77 - 74}{1.2274}

Z = 2.45

Z = 2.45 has a pvalue of 0.9929

X = 71

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

Z = \frac{71 - 74}{1.2274}

Z = -2.45

Z = -2.45 has a pvalue of 0.0071

0.9929 - 0.0071 = 0.9858

0.9858 = 98.58% probability of a random sample of size 150 yielding a sample mean of between 71 and 77.

c. A random sample of size 219 yielding a sample mean of less than 74.2

Sample size of 219 means that n = 219, s = \frac{15}{\sqrt{219}} = 1.0136

This probability is the pvalue of Z when X = 74.2. So

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

Z = \frac{74.2 - 74}{1.0136}

Z = 0.2

Z = 0.2 has a pvalue of 0.5793

0.5793 = 57.93% probability of a random sample of size 219 yielding a sample mean of less than 74.2

5 0
3 years ago
The function f(x) = x2 is transformed to f(x) = −1.4x2. Which statement describes the effect(s) of the transformation on the gra
Romashka-Z-Leto [24]

Answer:

C) The parabola is narrower and reflected across the x-axis.

Step-by-step explanation:

The original parabola has equation:

f(x) =  {x}^{2}

The transformed parabola has equation

f(x) =  - 1.4 {x}^{2}

How wide the graph is can be determined by the absolute value of the coefficient.

The smaller the absolute value of the coefficient, the wider the graph.

Since

|1|  \:  <  \:  | - 1.4|

The original graph is wider than the transformed graph.

Also the negative factor tells us there is a reflection in the x-axis.

3 0
3 years ago
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