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Hoochie [10]
2 years ago
12

Alejandro ran 15 3 over 10 yards during one play of a football game. During the next play, he ran 2 over 3 of that distance. How

many yards did he run during the second play?
A .10 1/5 yd
B .22 19/20 yd
C .5 1/10 yd
D .15 1/5 yd

Mathematics
2 answers:
goldfiish [28.3K]2 years ago
7 0
The answer to you’re question is definitely A. 10 1/5 yd
kodGreya [7K]2 years ago
6 0

Answer:

A: 10\frac{1}{5} YD

Here's what to do:

1. Change the mixed number to an improper fraction.

15  \frac{3}{10} = \frac{150}{10} + \frac{3}{10} =  \frac{153}{10}

2. Multiply the numerator by the other numerator that needs to be multiplied and do the same for the denominator. Here, let me explain.

\frac{153}{10} x \frac{2}{3}. When you muliply this, multiply the numerator by the numerator (153 x 2), and the denominator by the denominator (10 x 3). You should get your answer of \frac{306}{30} (because you put the product of the numerators in the numerator and the same for the denominator).

3. This is the correct answer, but you still need to convert this back to the numerator and simplify.

a. If you can use a calculator, just divide 306 by 30, and when you get 10.2, you know that 10.2 = 10 \frac{2}{10} = 10\frac{1}{5}

b. If you can't though, instead of 306, divide 300 by 30, which should give you 10, and add the remaining 6/30 (300/30 + 6/30 = 306/30, or the answer), which equals 2/10 which essentially equals 1/5, and you add the bolded numbers, which gives you 10\frac{1}{5}, or A.

Hope this helps :)

-jp524

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$7.00

Step-by-step explanation:

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Solving this for n, we get $7.00

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Answer:

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Step-by-step explanation:

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3 years ago
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Write an equation of the line that passes through the given points.<br><br> (-2,7) and (1,-2)
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4 years ago
Student scores on exams given by a certain instructor have mean 74 and standard deviation 14. This instructor is about to give t
Lapatulllka [165]

Answer:

P(\bar X >80)=P(Z>2.143)=1-P(z

Step-by-step explanation:

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

Let X the random variable that represent the Student scores on exams given by a certain instructor, we know that X have the following distribution:

X \sim N(\mu=74, \sigma=14)

The sampling distribution for the sample mean is given by:

\bar X \sim N(\mu,\frac{\sigma}{\sqrt{n}})

The deduction is explained below we have this:

E(\bar X)= E(\sum_{i=1}^{n}\frac{x_i}{n})= \sum_{i=1}^n \frac{E(x_i)}{n}= \frac{n\mu}{n}=\mu

Var(\bar X)=Var(\sum_{i=1}^{n}\frac{x_i}{n})= \frac{1}{n^2}\sum_{i=1}^n Var(x_i)

Since the variance for each individual observation is Var(x_i)=\sigma^2 then:

Var(\bar X)=\frac{n \sigma^2}{n^2}=\frac{\sigma}{n}

And then for this special case:

\bar X \sim N(74,\frac{14}{\sqrt{25}}=2.8)

We are interested on this probability:

P(\bar X >80)

And we have already found the probability distribution for the sample mean on part a. So on this case we can use the z score formula given by:

z=\frac{\bar X -\mu}{\frac{\sigma}{\sqrt{n}}}

Applying this we have the following result:

P(\bar X >80)=P(Z>\frac{80-74}{\frac{14}{\sqrt{25}}})=P(Z>2.143)

And using the normal standard distribution, Excel or a calculator we find this:

P(Z>2.143)=1-P(z

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