Really need help with this .

Mathematics

2 answers:

Elza [17]3 years ago

7 0

Answer:

216 square units

Step-by-step explanation:

Apparently, we're supposed to ignore the fact that the given geometry cannot exist. The short diagonal is too short to reach between the angles marked 98°. If Q and S are 98°, then R needs to be 110.13° or more for the diagonals to connect as described.

The equal opposite angles of 98° suggests that the figure is symmetrical about the diagonal RT. That being the case, diagonal RT will meet diagonal QS at right angles. Then the area is half the product of the lengths of the diagonals:

(1/2)×18×24 = 216 . . . . square units

_____

In a quadrilateral, the area can be computed as half the product of the diagonals and the sine of the angle between them. Here, we have assumed the angle to be 90°, so the area is simply half the product of diagonal measures.

lions [1.4K]3 years ago

6 0

Answer:

Step-by-step explanation:

The attached photo shows the diagram of quadrilateral QRST with more illustrations.

Line RT divides the quadrilateral into 2 congruent triangles QRT and SRT. The sum of the angles in each triangle is 180 degrees(98 + 50 + 32)

The area of the quadrilateral = 2 × area of triangle QRT = 2 × area of triangle SRT

Using sine rule,

q/SinQ = t/SinT = r/SinR

24/sin98 = QT/sin50

QT = r = sin50 × 24.24 = 18.57

Also

24/sin98 = QR/sin32

QR = t = sin32 × 24.24 = 12.84

Let us find area of triangle QRT

Area of a triangle

= 1/2 abSinC = 1/2 rtSinQ

Area of triangle QRT

= 1/2 × 18.57 × 12.84Sin98

= 118.06

Therefore, area of quadrilateral QRST = 2 × 118.06 = 236.12

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Lengths of full-term babies in the US are Normally distributed with a mean length of 20.5 inches and a standard deviation of 0.9

mash [69]

Answer:

66.48% of full-term babies are between 19 and 21 inches long at birth

Step-by-step explanation:

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.

Mean length of 20.5 inches and a standard deviation of 0.90 inches.

This means that $\mu = 20.5, \sigma = 0.9$