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dem82 [27]
3 years ago
14

There are 35 boys in sixth grade. The number of girls in the sixth grade is 42. Lonnie says that means the ratio of number of bo

ys in the sixth grade to number of girls in the sixth grade is 5:7. Is Lonnie correct? Show why or why not.
Mathematics
2 answers:
professor190 [17]3 years ago
7 0

Answer:

No.

Step-by-step explanation:

Ratio of any objects can be calculated by dividing the two objects with the common number.

Boys in the sixth grade = 35.

Girls in the sixth grade = 42.

Ratio of boys to girl = \frac{boys}{girls}

Ratio = \frac{35}{42}

Ratio = 5:6. (the numbers are divided by 7).

Thus, the ratio is 5:6 and not the 5:7.

Thus, Lonnie is not correct.

jolli1 [7]3 years ago
3 0
No... 35 divided by 7 is 5 and 42 divided 7 is 6 ... it should actually be 5:6
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An HP laser printer is advertised to print text documents at a speed of 18 ppm (pages per minute). The manufacturer tells you th
aliya0001 [1]

Answer:

0.227 = 22.7% probability that the mean printing speed of the sample is greater than 18.12 ppm.

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 17.42 ppm and a standard deviation of 3.25 ppm.

This means that \mu = 17.42, \sigma = 3.25

Sample of 12:

This means that n = 12, s = \frac{3.25}{\sqrt{12}}

Find the probability that the mean printing speed of the sample is greater than 18.12 ppm.

This is 1 subtracted by the p-value of Z when X = 18.12.

Z = \frac{X - \mu}{\sigma}

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{18.12 - 17.42}{\frac{3.25}{\sqrt{12}}}

Z = 0.75

Z = 0.75 has a pvalue of 0.773.

1 - 0.773 = 0.227

0.227 = 22.7% probability that the mean printing speed of the sample is greater than 18.12 ppm.

4 0
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Answer:

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Step-by-step explanation:

so (a+1) is the value of x

you can write it like this:

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using substitution, we can swap out all 'x's for 'a+1's. like so;

g(a+1)=5(a+1)-3  -- given

        =5a+5-3   --  distribute

        =5a+2      --  simplify!

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