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melamori03 [73]
2 years ago
15

Usually when Elena makes bird food, she mixes 9 cups of seeds with 6 tablespoons of maple syrup. However, today she is short on

ingredients. Think of a recipe that would yield a smaller batch of bird food but still taste the same. Explain or show your reasoning.
Mathematics
1 answer:
Delvig [45]2 years ago
7 0

Answer:

3 cups of seeds and 2 tablespoons of maple Syrup or 6 cups of seeds and 4 tablespoons of maple syrup.

Step-by-step explanation: As this is a ratio of 9:6: "for every 9 cups of seeds, there is 6 tablespoons of maple syrup"

The original ratio is 3:2 "for every 3 cups of seeds, there is 2 tablespoons of maple syrup"

Using this ratio, we can infer that 3:2 or 6:4 would be a simpler answer for this problem. If there is doubt, it would be better to use 3:2 as it is the smallest ratio.

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2

Step-by-step explanation:

slope =\frac{rise}{run}

\frac{rise}{run}=\frac{2}{1} =2

<em>good luck, i hope this helps :)</em>

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Find the unit rate of 42 teaspoons for 6 cups
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Here is an inequality: 7x+6/2 &lt; 3x +2
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7 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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