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meriva
3 years ago
11

Andrea is at the grocery store buying fruit for a smoothie stand. She needs 7 boxes of raspberries for every 5 bunches of banana

s she buys. The price of a box of raspberries is $2.50 and the price of a bunch of bananas is $3.00. The sales tax is 8%. Andrea has $135.00 to spend on fruit. What is the greatest number of boxes of raspberries and the greatest number of bunches of bananas Andrea can buy if the ratio of boxes of raspberries to bunches of bananas is 7:5? Be sure to show your work.
Mathematics
1 answer:
Degger [83]3 years ago
4 0

Answer:

The greatest number of bunches of bananas that Andrea can buy is 15 and the greatest number of boxes of raspberries that Andrea can buy is 21 to maintain the ratio 7:5

Step-by-step explanation:

Let

x ---->the greatest number of boxes of raspberries that Andrea can buy

y ---->the greatest number of bunches of bananas that Andrea can buy

we know that

100\%+8\%=106\%=108/100=1.08 ---> sales tax

\frac{x}{y} =\frac{7}{5}

x=\frac{7}{5}y ----> equation A

1.08[2.50x+3.00y]\leq 135 ----> inequality B

substitute equation A in the inequality B

1.08[2.50(\frac{7}{5}y)+3.00y]\leq 135

solve for y

Multiply by 5 both sides to remove the fraction

18.9y+16.2y\leq 675

35.1y\leq 675

y\leq 19.23

so

The maximum value of y is 19

Find the value of x

replace the value of y in equation A until you get an integer value that satisfies the ratio 7:5  

For y=19

x=\frac{7}{5}(19)

x=26.6

For y=18

x=\frac{7}{5}(18)

x=25.2

For y=17

x=\frac{7}{5}(17)

x=23.8

For y=16

x=\frac{7}{5}(16)

x=22.4

For y=15

x=\frac{7}{5}(15)

x=21

therefore

The greatest number of of bunches of bananas that Andrea can buy is 15 and the greatest number of boxes of raspberries that Andrea can buy is 21 to maintain the ratio 7:5

<u><em>Verify the inequality B</em></u>

1.08[2.50(21)+3.00(15)]\leq 135

1.08[52.5+45]\leq 135

105.3\leq 135 ----> is true

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The question is incomplete! Complete question along with answer and step by step explanation is provided below.

Question:

Most individuals are aware of the fact that the average annual repair cost for an automobile depends on the age of the automobile. A researcher is interested in finding out whether the variance of the annual repair costs also increases with the age of the automobile. A sample of 26 automobiles 4 years old showed a sample standard deviation for annual repair costs of $120 and a sample of 23 automobiles 2 years old showed a sample standard deviation for annual repair costs of $100. Let 4 year old automobiles be represented by population 1.

State the null and alternative versions of the research hypothesis that the variance in annual repair costs is larger for the older automobiles.

At a 0.01 level of significance, what is your conclusion? What is the p-value?

Answer:

Null hypotheses = H₀ = σ₁² ≤ σ₂²

Alternative hypotheses = Ha = σ₁² > σ₂²

Test statistic = 1.44

p-value = 0.1954

0.1954 > 0.01

Since the p-value is greater than the given significance level therefore, we cannot reject the null hypothesis.

We can conclude that there is no sufficient evidence to support the claim that the variance in annual repair costs is larger for older automobiles.

Step-by-step explanation:

Let σ₁² denotes the variance of 4 years old automobiles

Let σ₂² denotes the variance of 2 years old automobiles

State the null and alternative hypotheses:

The null hypothesis assumes that the variance in annual repair costs is smaller for older automobiles.

Null hypotheses = H₀ = σ₁² ≤ σ₂²

The alternate hypothesis assumes that the variance in annual repair costs is larger for older automobiles.

Alternative hypotheses = Ha = σ₁² > σ₂²

Test statistic:

The test statistic is given by

Test statistic = σ₁²/σ₂²

Test statistic = 120²/100²

Test statistic = 1.44

p-value:

The degree of freedom corresponding to 4 years old automobiles is given by

df₁ = n - 1  

df₁ = 26 - 1  

df₁ = 25

The degree of freedom corresponding to 2 years old automobiles is given by

df₂ = n - 1  

df₂ = 23 - 1  

df₂ = 22

Using Excel to find out the p-value,  

p-value = FDIST(F-value, df₁, df₂)

p-value = FDIST(1.44, 25, 22)

p-value = 0.1954

Conclusion:

When the p-value is less than the significance level then we reject the Null hypotheses

p-value < α   (reject H₀)

But for the given case,

p-value > α

0.1954 > 0.01

Since the p-value is greater than the given significance level therefore, we cannot reject the null hypothesis.

We can conclude that there is no sufficient evidence to support the claim that the variance in annual repair costs is larger for older automobiles.

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Step-by-step explanation:

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