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3 years ago

?????????????????help???

Mathematics

2 answers:

lisabon 2012 [21]3 years ago

6 0

Hello there!

Equivalent is something that is equal to another thing. Non-equivalent is obviously something that is not equation.

They give 2 fractions. In order to find out if they are equal or not, we must turn both of them into decimal.

How do you do that?

Well, just take your calculator then take the number on top (numerator) then divide by the number at the bottom (denominator).

3/5 = 0.6

7/23 = 0.30

Thus,

The fractions are Nonequivalent!

The correct answer is the first option.

I hope this answer is clear enough to understand. Let me know if you have any misunderstanding!

As always, I'm glad to be your helper!

Otrada [13]3 years ago

3 0

They are not equivalent fractions.

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Pherris is graphing the function f(x) = 2(3)x. He begins with the point (1, 6). Which could be the next point on his graph?

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the next point would be (2,18)

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3 years ago

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Jenny tweets 33 times a day. antonio posts 5 tweets per day. let d represent the number of given days. use an algebraic expressi

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Jenny's algebraic expression:

y = 33d

where y is the total number of posts

total tweets in 5 days

y = (33)(5)

y = 165 tweets

Antonio's expression:

y = 5d

total tweets in 5 days

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3 years ago

Choose the correct expressions using the fewest number of bases possible that are equivalent to the current expression. Select A

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<h3>2 Answers: Choice B, Choice C</h3>

The rule we use here is $\frac{a^b}{a^c} = a^{b-c}$

If the font size is too small, then it says (a^b)/(a^c) = a^(b-c)

We subtract the exponents when dividing exponentials like this. The bases must be the same.

So this means the exponents 13 and 3 subtract to get 13-3 = 10

We either have an exponent of "13-3" or an exponent of "10" as an equivalent expression. The base stays at 2 the entire time.

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3 years ago

medical tests. Task Compute the requested probabilities using the contingency table. A group of 7500 individuals take part in a

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Probabilities are used to determine the chances of an event

The probability that a person is sick is: 0.008
The probability that a test is positive, given that the person is sick is 0.9833
The probability that a test is negative, given that the person is not sick is: 0.9899
The probability that a person is sick, given that the test is positive is: 0.4403
The probability that a person is not sick, given that the test is negative is: 0.9998
A 99% accurate test is a correct test

(a) Probability that a person is sick

From the table, we have:

$\mathbf{Sick = 59+1 = 60}$

So, the probability that a person is sick is:

$\mathbf{Pr = \frac{Sick}{Total}}$

This gives

$\mathbf{Pr = \frac{60}{7500}}$

$\mathbf{Pr = 0.008}$

The probability that a person is sick is: 0.008

(b) Probability that a test is positive, given that the person is sick

From the table, we have:

$\mathbf{Positive\ and\ Sick=59}$

So, the probability that a test is positive, given that the person is sick is:

$\mathbf{Pr = \frac{Positive\ and\ Sick}{Sick}}$

This gives

$\mathbf{Pr = \frac{59}{60}}$

$\mathbf{Pr = 0.9833}$

The probability that a test is positive, given that the person is sick is 0.9833

(c) Probability that a test is negative, given that the person is not sick

From the table, we have:

$\mathbf{Negative\ and\ Not\ Sick=7365}$

$\mathbf{Not\ Sick = 75 + 7365 = 7440}$

So, the probability that a test is negative, given that the person is not sick is:

$\mathbf{Pr = \frac{Negative\ and\ Not\ Sick}{Not\ Sick}}$

This gives

$\mathbf{Pr = \frac{7365}{7440}}$

$\mathbf{Pr = 0.9899}$

The probability that a test is negative, given that the person is not sick is: 0.9899

(d) Probability that a person is sick, given that the test is positive

From the table, we have:

$\mathbf{Positive\ and\ Sick=59}$

$\mathbf{Positive=59 + 75 = 134}$

So, the probability that a person is sick, given that the test is positive is:

$\mathbf{Pr = \frac{Positive\ and\ Sick}{Positive}}$

This gives

$\mathbf{Pr = \frac{59}{134}}$

$\mathbf{Pr = 0.4403}$

The probability that a person is sick, given that the test is positive is: 0.4403

(e) Probability that a person is not sick, given that the test is negative

From the table, we have:

$\mathbf{Negative\ and\ Not\ Sick=7365}$

$\mathbf{Negative = 1+ 7365 = 7366}$

So, the probability that a person is not sick, given that the test is negative is:

$\mathbf{Pr = \frac{Negative\ and\ Not\ Sick}{Negative}}$

This gives

$\mathbf{Pr = \frac{7365}{7366}}$

$\mathbf{Pr = 0.9998}$

The probability that a person is not sick, given that the test is negative is: 0.9998

(f) When a test is 99% accurate

The accuracy of test is the measure of its sensitivity, prevalence and specificity.

So, when a test is said to be 99% accurate, it means that the test is correct, and the result is usable; irrespective of whether the result is positive or negative.