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denpristay [2]
3 years ago
7

to fill a coffee mug at a local shop costs $2.50. the shop sells coffee beans foe $12 per pound. each pound makes enough coffee

to fill the mug 100 times. approximately how many times greater is the cost of drinking the coffee at the local shop compared to drinking at home?
Mathematics
1 answer:
myrzilka [38]3 years ago
3 0

Answer:

There are a few possible answers so read explanation, but the one I will put up here is:

20.83

Step-by-step explanation:

First you have to find how much 100 cups of coffee costs in store.

To do this you will multiply 2.50 by 100 and get 250. So now we know 100 cups of coffee in store costs $250 whereas 100 cups at home is $12.

To find how many times greater the price in store is compared to the at home brew, you have to divide 250 by 12 and get 20.8333333....

We don't stop there though, because it asks us to approximate. I am not sure what it would like us to round to, but here are some possible approximations:

  1. 20.83
  2. 20.8
  3. 21

Any of those re reasonable approximations, you choose whichever you think the question wants, or whatever your teacher asks for.

Hope this helps

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Answer:

Step-by-step explanation:

Hello!

The research team created a cracker with fewer calories. The average content of calories of the new crackers per serving of 6 should be less than 60.

To test it a random sample of 26 samples of the new cracker was taken and the calories per serving were measured.

Then the study variable is

X: calories of a 6 serve sample of the new reduced-calorie version. (cal)

The variable has a normal distribution with a population standard deviation of 0.82 cal.

To test the claim that the new crackers have on average less than 60 calories, the parameter of interest is the population mean (μ) and the hypotheses are:

H₀: μ ≥ 60

H₁: μ < 60

α: 0.01

Since the variable has a normal distribution and the population variance is known, the best statistic to use to conduct the test is a Standard Normal

Z= \frac{(X[bar]-Mu)}{\frac{Sigma}{\sqrt{n}}  } ~N(0;1)

This test is one tailed to the left, wich means that the null hypothesis will be rejected at low levels of the statistic.

Z_{\alpha } = Z_{0.01} = -2.334

If Z ≤ -2.334, the decision is to reject the null hypothesis.

If Z > -2.334, the decision is to not reject the null hypothesis.

Using the data of the sample I've calculated the sample mean.

X[bar]= ∑X/n= 1548.61/26= 59.56 cal

Z_{H_0}= \frac{(59.56-60)}{\frac{0.82}{\sqrt{26} } } = -2.736

The observed Z value is less than the critical value, so the decision is to reject the null hypothesis.

At a level of significance of 1%, you can conclude that the population mean of calories of the samples of new crackers is less than 60 cal.

I hope it helps!

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