When adding two mixed numbers, you should add the ignore the fractions and add the mixed numbers first.

erastova [34]

Reducing to lowest terms simply means dividing both the numerator and the denominator by the same amount so as to get an equivalent fraction that has lower numbers so it looks nicer.

For example, we know that 1/4 = 2/8 = 4/16 = 10/40.

So for 18/32, let's start by diving both numbers by 2, to give 9/16. 9 and 16 can't be divided by the same number so 18/32 in it's lowest terms is 9/16.

6 0

3 years ago

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Assume LaTeX: \angle∠A and LaTeX: \angle∠B are complementary. Find mLaTeX: \angle∠A if it is 14 more than LaTeX: \angle∠B.

Alex787 [66]

Answer:

$A = 52$

Step-by-step explanation:

Given

$A = 14 + B$

Required

Find A

Since both angles are complementary; then:

$A + B = 90$

Solve for B in $A = 14 + B$

$B = A - 14$

Substitute $B = A - 14$ in $A + B = 90$

$A + A - 14 = 90$

$2A - 14 = 90$

Solve for 2A

$2A = 90 + 14$

$2A = 104$

Solve for A

$A = 104/2$

$A = 52$

3 0

2 years ago

Company A offers unlimited minutes and hacks for a flat fee of $50 per month and charges $1.50 for each GB of data used per mont

GREYUIT [131]

F(x) = 1.5x + 50

if you use 5GB per month, you should pay
f(5) = 1.5(5) + 50 = $57.50

4 0

3 years ago

19. A sample of 50 retirees is drawn at random from a normal population whose mean age and standard deviation are 75 and 6 years

Juliette [100K]

Answer:

a) Approximately normal.

b) The mean is 75 years and the standard deviation is 0.8485 years.

c) 0.9909 = 99.09% probability that the mean age exceeds 73 years

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 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.

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