What is 8/12 + A/12=2/b

Identify the % of change as an increase or decrease.

Verizon [17]

It is a percent increase and it increased by 15%

I got this answer by doing 24.61/21.40 which equals 1.15

You can check this answer by doing 21.40 * .15 on a calculator and when you do this you get 3.21 which you can then add back to 21.40 to get $24.61

4 0

3 years ago

Marc Gasol scored 18 points on Monday, 29 points on Wednesday, and 8 points on Saturday. What

laila [671]

Answer: 18.33 ppg

Step-by-step explanation:

He played three games

18+29+8=55

55/3=18.33

7 0

2 years ago

1. The figure shows a graph of the function of f(x) in the xy-coordinate plane, with the vertex at (1,9) and the zeros

never [62]

Answer:

f{0) is greater than g(0) and f(2) is greater than g(2).

Step-by-step explanation:

f{0) is greater than g(0) = f(0)=8 and g(0)=2

f(2) is greater than g(2) = f(2)=8 and g(2)= -4

3 0

3 years ago

Ricardo and Tammy practice putting golf balls. Ricardo makes 47% of his putts and Tammy makes 51% of her putts. Suppose that Ric

yaroslaw [1]

Answer:

0.3821 = 38.21% probability that Ricardo makes a higher proportion of putts than Tammy.

Step-by-step explanation:

To solve this question, we need to understand the normal distribution, the central limit theorem, and subtraction of normal variables.

Normal probability distribution

When the distribution is normal, we use 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

Subtraction of normal variables:

When we subtract normal variables, the mean of the subtraction will be the subtraction of the means, while the standard deviation will be the square root of the sum of the variances.

Ricardo makes 47% of his putts, and attempts 25 putts.

By the Central Limit Theorem, we have that:

$\mu_R = 0.47, s_R = \sqrt{\frac{0.47*0.53}{25}} = 0.0998$