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2 years ago

GEOMETRY HELP!!!!!!!! Why is he wrong?

Mathematics

2 answers:

Mademuasel [1]2 years ago

8 0

Answer:

He is wrong since reflecting the image across the x-axis means reflecting it on the axis that is horizontal and reflecting it over the y-axis means reflecting it on the y-axis which is verticle.

AleksandrR [38]2 years ago

6 0

Answer:No, it would not be the same if you reflect it from the X axis.

Step-by-step explanation:

because the the shape is not "on" the X axis. When you reflect the shape across the X axis, then you will not really get a shape. It's easier if you imagine you put a mirror on the x axis and looked at it. Malik would have to shift the whole shape down so that the current points (3,1) and (-3,1) would change to (3,0) and (-3,0) Also shifting down the other two points too. Reflecting it is like if you had the shape in paper and you folded it in half. If it matches perfectly, then you know that you have a match and that it is reflecting. If it doesn't fold perfectly, then it doesn't reflect. So if you folded the shape from the X axis, you wouldn't get a perfect match so he is wrong. Does it help?

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How to find n for F=n/4+37

Alla [95]

Answer: F=40 or other words n=40

Step-by-step explanation:

F= n/4 + 37

F= 12/4 + 37

F= 3 +37

F =40

Hope this helped! ;)

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2 years ago

Find the general solution of the given differential equation. y'' + 2y' + 5y = 3 sin 2t

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2 years ago

A selective university advertises that 96% of its bachelor’s degree graduates have, on graduation day, a professional job offer

OLEGan [10]

Answer:

The probability is $P( p < 0.9207) = 0.0012556$

Step-by-step explanation:

From the question we are told

The population proportion is $p = 0.96$

The sample size is $n = 227$

The number of graduate who had job is k = 209

Generally given that the sample size is large enough (i.e n > 30) then the mean of this sampling distribution is

$\mu_x = p = 0.96$

Generally the standard deviation of this sampling distribution is

$\sigma = \sqrt{\frac{p (1 - p )}{n} }$

=> $\sigma = \sqrt{\frac{0.96 (1 - 0.96 )}{227} }$

=> $\sigma = 0.0130$

Generally the sample proportion is mathematically represented as

$\^ p = \frac{k}{n}$

=> $\^ p = \frac{209}{227}$

=> $\^ p = 0.9207$

Generally probability of obtaining a sample proportion as low as or lower than this, if the university’s claim is true, is mathematically represented as

$P( p < 0.9207) = P( \frac{\^ p - p }{\sigma } < \frac{0.9207 - 0.96}{0.0130 } )$