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3 years ago

Which method would prove the quadrilateral is a parallelogram?

Mathematics

1 answer:

Maurinko [17]3 years ago

3 0

Answer:

Answer: Each pair of opposite sides has the same measure. Therefore, they are congruent. If both pairs of opposite sides of a quadrilateral are congruent, the quadrilateral is a parallelogram.

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Katie wants to buy 27 candles. If there are 9 candles in each box, how many boxes of candles should Katie buy? * (need the answe

cricket20 [7]

Answer:

3 boxes

Step-by-step explanation:

because 3 times 9 is 27.

3 0

3 years ago

Read 2 more answers

Help me with this problem? 15 points

kobusy [5.1K]

Answer:

See explanation

Step-by-step explanation:

Since 12 is 3 times greater than 4, you simply need to divide all of the ingredients by 3.

Cactus chunks: 4 1/2 divided by 3 is 3/2 or 1 1/2

Crushed Tumbleweed: 8/3 is just 8/3 or 2 2/3

Cactus Juice: 10/4 or 2 1/2

Lizard eggs: 4

Crumbled Flower Petals: 7/4 or 1 3/4

Water: 10/3 or 3 1/3

Hope this helps!

5 0

3 years ago

Can y’all please explain this to me, I know the answer but I don’t know how to get it thanks

EleoNora [17]

Answer:

250 jars

6 hours

Step-by-step explanation:

We know they make 50 jars in an hour, so 50 times 5 is 250 jars in 5 hours. Since 300 is 50 more than 250, and we know 50 times 6 is 300, we can say that we would need 6 hours to make 300 jars.

8 0

3 years ago

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

uysha [10]

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.