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nikklg [1K]
3 years ago
6

A cone-shaped water cup has a height of 3.3 inches and a diameter of 2.7 inches. One fluid ounce is equivalent to 1.8 cubic inch

es. What is the capacity, in fluid ounces, of the cup? Use 3.14 for π. Round to the nearest tenth.
Mathematics
2 answers:
DaniilM [7]3 years ago
8 0

Answer:

3.5 fluid ounces

Step-by-step explanation:

In this question, we are asked to calculate the capacity in fluid ounce of a cone-shaped cup.

To solve this, we need to calculate the volume of the cup.

Mathematically, the volume of a cone =

1/3 * π * r^2 * h

Where r = d/2 = 2.7/2 = 1.35 inches

h = 3.3 inches

By substituting this, we have

V = 1/3 * 3.14 * 1.35^2 * 3.3 = 6.3 cubic inch

Now we proceed to calculate the capacity

From the question, we are told that ;

1 fluid ounce = 1.8 cubic inch

This means

x fluid ounce = 6.3 cubic inch

x = 6.3/1.8

x = 3.5 fluid ounces

anygoal [31]3 years ago
5 0

Answer:

about 3.5

Step-by-step explanation:

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Since 600 ÷ 6 = 100 and 593 is less than 6, 593 ÷ 6 is a little less than 100.

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4 0
3 years ago
The average yield of the standard variety off soybeans per acre on a farm in a region is 48.8 bushels per acre, with a standard
I am Lyosha [343]

Answer:

z=\frac{53.4-48.8}{\frac{12}{\sqrt{36}}}=2.3  

p_v =P(Z>2.3)=1-P(Z  

If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 48.8 at 1% of signficance.  

Step-by-step explanation:

1) Data given and notation  

\bar X=53.4 represent the sample mean

\sigma=12 represent the population standard deviation assumed

n=36 sample size  

\mu_o =48.8 represent the value that we want to test  

\alpha=0.01 represent the significance level for the hypothesis test.  

z would represent the statistic (variable of interest)  

p_v represent the p value for the test (variable of interest)  

2) State the null and alternative hypotheses.  

We need to conduct a hypothesis in order to check if the true mean is higher than 48.8, the system of hypothesis would be:  

Null hypothesis:\mu \leq 48  

Alternative hypothesis:\mu > 48  

Since we assume that know the population deviation, is better apply a z test to compare the actual mean to the reference value, and the statistic is given by:  

z=\frac{\bar X-\mu_o}{\frac{\sigma}{\sqrt{n}}} (1)  

z-test: "Is used to compare group means. Is one of the most common tests and is used to determine if the mean is (higher, less or not equal) to an specified value".  

3) Calculate the statistic  

We can replace in formula (1) the info given like this:  

z=\frac{53.4-48.8}{\frac{12}{\sqrt{36}}}=2.3  

4)P-value  

Since is a right tailed test the p value would be:  

p_v =P(Z>2.3)=1-P(Z  

5) Conclusion  

If we compare the p value and the significance level given \alpha=0.01 we see that p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, so we can conclude that the true mean is not significantly higher than 48.8 at 1% of signficance.  

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loris [4]

Angle G = 130 degrees

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<u>Angle G would be 130 degrees</u> because it's a vertical angle, and vertical angles are always alike.

<u>Angle H would be 50 degrees</u> because it's an adjacent angle, and we also know that one side of the line is always 180 degrees so we have an equation that looks like this 180 - 130 = 50 degrees

<u>Angle K would be 74 degrees</u> because it's a vertical angle.

<u>Angle M would be 106 degrees</u> because it's an adjacent angle.

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There answer is 120
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