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Black_prince [1.1K]
2 years ago
8

Li wants to add these items to her suitcase: a hairdryer (1.25 lb), a hand-held video game (0.6 lb), an extra video game (0.25 l

b), and a music player (0.4 lb). Using the inequality x ≤ 2.25, can she add all these items to the suitcase? If not, what could be left out to be closest to the maximum weight allowed? Explain.
Her suitcase already is 47.75 with a 50 lbs limit. There is an extra fee once you go past the limit

PLZ HELP!!
Mathematics
2 answers:
lbvjy [14]2 years ago
7 0
Add some of them or all of them to your sum of 47.75, if either or exceeds the limit then that is what left out.
Rzqust [24]2 years ago
6 0

The total weight of the items is 1.25 + 0.25 + 0.6 + 0.4 = 2.5 lb. 2.5 is 0.25 greater than 2.25, so not all the items can be added. If Li leaves out the extra game, which weighs 0.25 lb, she’d have the greatest possible weight allowed.

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Answer:

0.04

Step-by-step explanation:

In this case we must use the following formula to be able to find the standard error, which would be the square root, of the probability for its complement divided by the population:

SE= \sqrt{\frac{p *(1-p)}{n} } \\

Now, knowing that p = 0.552 and n = 160 we replace and we are left with:

SE =  \sqrt{\frac{0.552 *(1-0.552)}{160} } \\

SE = \sqrt{0.00154}

SE = 0.039

Which means that the standard error of the proportion is 0.04

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2 years ago
A liquid dietary product implies in its advertising that use of the product for one month results in an average weight loss of a
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Answer:

Following are the responses to the given question:

Step-by-step explanation:

Please find the table in the attached file.

mean and standard deviation difference: \bar{d}=\frac{\Sigma d}{n} =\frac{-4-6-.......-4-4}{8}=-4.125 \\\\S_d=\sqrt{\frac{\Sigma (d-\bar{d})^2 }{n-1}}=\sqrt{\frac{(-4 + 4.125)^2 +.......+(-4 +4.125)^2 }{8-1}}= 1.246

For point a:

hypotheses are:

H_0 : \mu_d \geq -3\\\\H_a : \mu_d < -3\\\\

degree of freedom:

df=n-1=8-1=7

 From t table, at\alpha = 0.05, reject null hypothesis if t.

test statistic:  

t=\frac{\bar{d}-\mu_d }{\frac{s_d}{\sqrt{d}}}=\frac{ -4.125- (-3)}{\frac{1.246}{ \sqrt{8}}} =-2.55

because the t=-2.553, removing the null assumption. Data promotes a food product manufacturer's assertion with a likelihood of Type 1 error of 0.05.

For point b:

From t table, at \alpha =0.01, removing the null hypothesis if t.

because t=-2.553 >-2.908, fail to removing the null hypothesis.  

The data do not help the foodstuff producer's point with the likelihood of a .01-type mistake.

For point c:

Hypotheses are:

H_0: \mu_d \geq -5\\\\H_a: \mu_d < -5

Degree of freedom:

df=n-1=8-1=7

From t table, at \alpha =0.05, removing the null hypothesis if t.

test statistic:  t=\frac{\bar{d}-\mu_d}{\frac{s_d}{\sqrt{n}}} =\frac{-4.125-(-5)}{\frac{1.246}{\sqrt{8}}}=1.986

Since t-1.986 >-1.895, The null hypothesis fails to reject. The results do not support the packaged food producer's claim with a Type 1 error probability of 0,05.

From t table, at\alpha= 0.01, reject null hypothesis ift.

Since t=1.986>-2.998 , fail to reject null hypothesis.  

Data do not support the claim of the producer of the dietary product with the probability of Type 1 error of .01.

5 0
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Answer:

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Step-by-step explanation:

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Now, let us assume:

n : the number of times the paper is folded.

y : The number of parts obtained after folds.

Now, if the paper if folded ONCE ⇒  n = 1

Also, when the pap er is folded once, the parts obtained are TWO equal parts.

⇒  for n = 1 , y = 2       ..... (1)

Similarly, if the paper if folded TWICE  ⇒  n = 2

Also, when the paper is folded twice, the parts obtained are FOUR equal parts.

⇒  for n = 2 , y = 4       ..... (2)

⇒y  = 2^2  =  2^n

Continuing the same way, if the paper is folded SEVEN times  ⇒  n = 7

So, y = 2^ n = 2^7 = 128

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Lastly,  if the paper is folded ELEVEN  times  ⇒  n = 11

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