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kari74 [83]
3 years ago
7

How can parallel lines be used to compare figures E and F? Explain your reasoning.

Mathematics
1 answer:
Aneli [31]3 years ago
3 0

Answer:

The similarities are

1) The length of E and F can be described by two parallel lines spaced 3 blocks apart where the parallel line on the left of both E and F is 2 blocks long, while the parallel line on the right is one block long

2) Both height of E and F can be described by two parallel lines spaced 2 blocks apart  where the parallel line on the top of both E and F is 3 blocks long, while the parallel line at the bottom is one block long

3) The interior of E an F can be described by parallel lines 2 blocks long in the horizontal portion and one block long in the vertical portion

The differences are

1) The difference between E and F is that the parallel lines used for the construction of E are all one block higher than that of F

2) The other difference is that all the lines used for the construction of the figure E are 3 blocks to the left of those used for the construction of F

Figure F is essentially the translation of figure E three blocks to right and one block down

Step-by-step explanation:

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Determine the mean absolute deviation of the data.9, 7, 11, 10, 8
Darya [45]

Answer:

mean=average which means you add all of the numbers and divide by the number of numbers there are, which sounds pretty confusing, but i'll show you! 9+7+11+10+8=45, now you divide 45 by 5, which is how many numbers there are that we had to add. 45 divided by 5 is 9, which means the MEAN/average is 9!

Step-by-step explanation:

hope this helps!

5 0
3 years ago
Find f(−2) given that f(x)=2x2−3x+7.
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Answer:

21.

Step-by-step explanation:

f(x) = 2x^2 - 3x + 7.

When x = -2,

f(-2) = 2(-2)^2 - 3(-2) + 7

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Which two properties of equality could Zoe use to finish solving for x
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4 0
3 years ago
What is the solution to the following system of equations? x+2y=2 x-2y=-2
Tcecarenko [31]
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7 0
3 years ago
We are conducting a hypothesis test to determine if fewer than 80% of ST 311 Hybrid students complete all modules before class.
Juli2301 [7.4K]

Answer:

z=\frac{0.881 -0.8}{\sqrt{\frac{0.8(1-0.8)}{110}}}=2.124  

Null hypothesis:p\geq 0.8  

Alternative hypothesis:p < 0.8  

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

p_v =P(Z  

So the p value obtained was a very high value and using the significance level assumed \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis.

Be Careful with the system of hypothesis!

If we conduct the test with the following hypothesis:

Null hypothesis:p\leq 0.8  

Alternative hypothesis:p > 0.8

p_v =P(Z>2.124)=0.013  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis.

Step-by-step explanation:

1) Data given and notation  

n=110 represent the random sample taken

X=97 represent the students who completed the modules before class

\hat p=\frac{97}{110}=0.882 estimated proportion of students who completed the modules before class

p_o=0.8 is the value that we want to test

\alpha represent the significance level

z would represent the statistic (variable of interest)

p_v{/tex} represent the p value (variable of interest)  2) Concepts and formulas to use  We need to conduct a hypothesis in order to test the claim that the true proportion is less than 0.8 or 80%:  Null hypothesis:[tex]p\geq 0.8  

Alternative hypothesis:p < 0.8  

When we conduct a proportion test we need to use the z statistic, and the is given by:  

z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}} (1)  

The One-Sample Proportion Test is used to assess whether a population proportion \hat p is significantly different from a hypothesized value p_o.

3) Calculate the statistic  

Since we have all the info requires we can replace in formula (1) like this:  

z=\frac{0.881 -0.8}{\sqrt{\frac{0.8(1-0.8)}{110}}}=2.124  

4) Statistical decision  

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.  

The significance level assumed \alpha=0.05. The next step would be calculate the p value for this test.  

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

p_v =P(Z  

So the p value obtained was a very high value and using the significance level assumed \alpha=0.05 we have p_v>\alpha so we can conclude that we have enough evidence to FAIL to reject the null hypothesis.

Be Careful with the system of hypothesis!

If we conduct the test with the following hypothesis:

Null hypothesis:p\leq 0.8  

Alternative hypothesis:p > 0.8

p_v =P(Z>2.124)=0.013  

So the p value obtained was a very low value and using the significance level assumed \alpha=0.05 we have p_v so we can conclude that we have enough evidence to reject the null hypothesis.

5 0
3 years ago
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