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eimsori [14]
2 years ago
7

Use the proportion below to determine 30% of 20.

Mathematics
1 answer:
mestny [16]2 years ago
6 0

Answer:

x=6

Step-by-step explanation:

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Whats 1-2x+3y for x=-2 and y=-5 ?​
lawyer [7]

Answer:

-10

Step-by-step explanation:

2*-2=-4

3*-5=-15

1-(-4)+(-15)=-10

5 0
3 years ago
What is the unit rate for 1/2 a cup for 4 recipes
VMariaS [17]
1/8 cupe for 1 recipe
1/8 • 4 = 4/8 = 1/2

Brainliest?
8 0
2 years ago
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You flipped a coin 50 times and got 23 heads.What is the experimental probability of getting a head? Write your answer as a frac
lys-0071 [83]

Answer:

23/50, 0.46, and 46%

Step-by-step explanation:


This problem is stating that every fifty times you flip a coin you get 23 heads. Finding the fraction is simple, it would be 23/50 because it is expressing the probability. The problem clearly states that every 50 times you get 23 heads. To find the decimal, take the fraction, 23/50, and multiply the numerator and denominator by 2. you get 46/100 which is 0.46. A percent is just a fraction out of a 100 which would make the percent 46.


8 0
3 years ago
Two factors of 24 that add up to 11
Vadim26 [7]
Simple....

8*3=24

8+3=11

Thus, your answer.
8 0
3 years ago
A manufacturer must test that his bolts are 4.00 cm long when they come off the assembly line. He must recalibrate his machines
storchak [24]

Answer:

The null hypothesis is H_o: \mu = 4.

The alternate hypothesis is H_a: \mu \neq 4

The pvalue of the test is 0.0182 < 0.05, which means that there is sufficient evidence to show that the manufacturer needs to recalibrate the machines.

Step-by-step explanation:

A manufacturer must test that his bolts are 4.00 cm long when they come off the assembly line.

This means that the null hypothesis is that they are 4.00 cm long, that is:

H_o: \mu = 4

At the alternate hypothesis we test if it is different. So

H_a: \mu \neq 4

The test statistic is:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

In which X is the sample mean, \mu is the value tested at the null hypothesis, \sigma is the standard deviation and n is the size of the sample.

4 is tested at the null hypothesis:

This means that \mu = 4

After sampling 196 randomly selected bolts off the assembly line, he calculates the sample mean to be 4.14 cm.

This means that n = 196, X = 4.14

He knows that the population standard deviation is 0.83 cm.

This means that \sigma = 0.83

Value of the test statistic:

z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}

z = \frac{4.14 - 4}{\frac{0.83}{\sqrt{196}}}

z = 2.36

Pvalue of the test and decision:

The pvalue of the test is the probability that the sample mean is different by at least 4.14 - 4 = 0.14 from the target value, which is P(|z| > 2.36), which is 2 multiplied by the pvalue of z = -2.36.

Looking at the z-table, z = -2.36 has a pvalue of 0.0091

2*0.0091 = 0.0182

The pvalue of the test is 0.0182 < 0.05, which means that there is sufficient evidence to show that the manufacturer needs to recalibrate the machines.

5 0
2 years ago
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