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Alona [7]
4 years ago
9

Lilly and Maggie decorated their windows with twinkle lights. Maggie used 51 more twinkle lights than Lilly. Fill in the box wit

h the expression that represents the amount of twinkle lights Maggie used. Let m represent the amount of twinkle lights Maggie used and l represent the amount of twinkle lights Lilly used.If Lilly used 70 twinkle lights, how many twinkle lights did Maggie use?
Mathematics
1 answer:
nadya68 [22]4 years ago
6 0
We know that
m-------------------- > <span>the amount of twinkle lights Maggie used
l--------------------- >  </span><span>the amount of twinkle lights Lilly used
l=70
m=51+l
therefore
m=51+70=121
m=121

the answer is 121 (</span>amount of twinkle lights Maggie used)
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3 years ago
Based on historical data, your manager believes that 26% of the company's orders come from first-time customers. A random sample
scoundrel [369]

Answer:

\hat p \sim N( p, \sqrt{\frac{p (1-p)}{n}})

And we can use the z score formula given by:

z = \frac{\hat p -\mu_p}{\sigma_p}

And if we find the parameters we got:

\mu_p = 0.26

\sigma_p = \sqrt{\frac{0.26(1-0.26)}{158}} = 0.0349

And we can find the z score for the value of 0.4 and we got:

z = \frac{0.4-0.26}{0.0349}= 4.0119

And we can find this probability:

P(z>4.0119) = 1-P(z

And if we use the normal standard table or excel we got:

P(z>4.0119) = 1-P(z

Step-by-step explanation:

For this case we have the following info given:

p = 0.26 represent the proportion of the company's orders come from first-time customers

n=158 represent the sample size

And we want to find the following probability:

p(\hat p >0.4)

And we can use the normal approximation since we have the following two conditions:

1) np = 158*0.26 = 41.08>10

2) n(1-p) = 158*(1-0.26) = 116.92>10

And for this case the distribution for the sample proportion is given by:

\hat p \sim N( p, \sqrt{\frac{p (1-p)}{n}})

And we can use the z score formula given by:

z = \frac{\hat p -\mu_p}{\sigma_p}

And if we find the parameters we got:

\mu_p = 0.26

\sigma_p = \sqrt{\frac{0.26(1-0.26)}{158}} = 0.0349

And we can find the z score for the value of 0.4 and we got:

z = \frac{0.4-0.26}{0.0349}= 4.0119

And we can find this probability:

P(z>4.0119) = 1-P(z

And if we use the normal standard table or excel we got:

P(z>4.0119) = 1-P(z

8 0
3 years ago
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Answer:

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Step-by-step explanation:

E[X+Y] = E[X] + E[Y]

E[X] is the average of X  or expectancy of X

E[Y] is the average or expectancy f Y

E[X] = 40P(student is in bus 1)+33P(student is in bus 2)+25P(student is in bus 3)+50P(student is in bus 4)=

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E[Y] = (number of students)/(number of drivers) = 148/4 = 37

So E[X+Y] = 39.2838 + 37 = 76.2838

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4 years ago
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