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Angles A and B are complementary. If sin A = 4x + 10 and cos B = 2x + 16, what is the value of x? (1 point) 3 4 13 22

olga_2 [115]

Answer: 3

Step-by-step explanation:

The sine of an angle is equal to the cosine of its complement, so

$4x+10=2x+16\\\\2x+10=16\\\\2x=6\\ \\ x=3$

5 0

2 years ago

Lu is making a quilt that is 20 squares wide and has 18 rows the border of the quilt is made by using each toy design equally as

mixer [17]

Answer:

The correct answer is two designs are used 12 times each and other four designs are used for 13 times each.

Step-by-step explanation:

Width of the quilt Lu is making is 18 rows of 20 squares each.

Thus the perimeter of the quilt is 20 + 20 + 18 + 18 = 76.

We can also say there are 76 square as the boundary which are to be bordered with toy designs.

Each square can hold 1 design of toy and there are 6 different designs of toys.

Thus number of times each design is used $\frac{76}{6}$ = 12 $\frac{4}{6}$ .

Thus there are two designs used 12 times each and other four designs are used for 13 times each.

3 0

3 years ago

The mean rent of a 3-bedroom apartment in Orlando is $1300. You randomly select 10 apartments around town. The rents are normall

lana [24]

Answer:

96.49% probability that the mean rent is more than $1100

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 normally distributed samples are solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore 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 pvalue, 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 $s = \frac{\sigma}{\sqrt{n}}$ .