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Mashutka [201]
3 years ago
15

Maria needs to buy shoes for $50, jeans for $40, and a shirt for $20. She has a coupon that gives her a discount of x percent on

shoes. She has a second coupon that gives her a discount of y percent on jeans. The third coupon gives her a discount of z percent on her total purchase. She cannot combine the coupon for the total purchase with the other two coupons. These expressions give both possibilities for the total cost of Maria's purchase after the coupons are applied, the variables represent the percentages as decimals.
Mathematics
2 answers:
Colt1911 [192]3 years ago
8 0
(50-(x*50))+(40-(y*40))+20= discounted with 2 coupons

110-(z*110)= the price with the total coupon. 

I believe these are the correct answers

damaskus [11]3 years ago
8 0

A. Which part of the expression represents the price of the shoes after a coupon was applied directly to them?

(1-x)

B. Which part of the expression represents the price of the shoes, jeans, and shirt before the total discount is applied?

(50+40+20)

C. Which part of the expression represents the percent that she will pay for the jeans if he uses the jeans coupon?

(1-y)

Please let me know if any of these answers were wrong, Thanks!

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Alternative hypothesis:p \neq 0.4

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Step-by-step explanation:

Information given

n=144 represent the random sample taken

X=81 represent the number of people with type A blood

\hat p=\frac{81}{144}=0.5625 estimated proportion of  people with type A blood

p_o=0.4 is the value that we want to verify

\alpha=0.01 represent the significance level

z would represent the statistic

p_v{/tex} represent the p value Hypothesis to testWe want to test if the percentage of the population having type A blood is different from 40%.:  Null hypothesis:[tex]p=0.4  

Alternative hypothesis:p \neq 0.4  

the statistic is given by:

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

Replacing the info given we got:

z=\frac{0.5625 -0.4}{\sqrt{\frac{0.4(1-0.4)}{144}}}=3.98  

Now we can calculate the p value with this probability taking in count the alternative hypothesis:

p_v =2*P(z>3.98)=0.0000689  

Since the p value is very low compared to the significance level we have enough evidence to reject the null hypothesis and we can conclude that the true percent of people with type A of blood is significantly different from 0.4 or 40%

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