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3 years ago

Can someone pls help me

Mathematics

1 answer:

harina [27]3 years ago

3 0

Answer:

16:8 2:1

Step-by-step explanation:

it's both 8 and 4 times 2 on each side, and then divided on each side

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8. Line ZX and Line WY are secants of circle V, as shown below.

lisabon 2012 [21]

Answer: take a protractor to the unkown sides to find the angle degrees and to check add them up and see if it is 360 degrees

Step-by-step explanation:

6 0

3 years ago

PLEASE HELP QUICK

aleksandrvk [35]

Answer:

A conditional statement is something like:

If P, then Q.

P = hypothesis.

Q = conclusion.

In this case, we have:

"If a polygon is a quadrilateral, then it is a square".

1) The hypothesis is: a polygon is a quadrilateral

2) The conclusion is: it is a square

3) It is not true, because there are other quadrilaterals that are not squares, for example, the rectangles.

4) The inverse of a conditional statement is (using the same notation than above)

If not P, then not Q.

In this case is:

"If a polygon is not a quadrilateral, then it is not a square"

(this is true)

5) A converse statement is:

If Q, then P

In this case is:

"if it is a square, then the polygon is a quadrilateral"

(Also true)

6) A biconditional statement is written as:

P if and only if Q.

In this case is:

A polygon is a quadrilateral if and only if it is a square.

(This is false)

3 0

3 years ago

For patients who have been given a diabetes test, blood-glucose readings are approximately normally distributed with mean 127 mg

zysi [14]

Answer:

Between the lower-bound of 117 mg/dl and the upper bound of 137 mg/dl.

Step-by-step explanation:

Empirical Rule

The Empirical Rule states that, for a normally distributed random variable:

Approximately 68% of the measures are within 1 standard deviation of the mean.

Approximately 95% of the measures are within 2 standard deviations of the mean.

Approximately 99.7% of the measures are within 3 standard deviations of the mean.

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 $s = \frac{\sigma}{\sqrt{n}}$ .