Help help help help help help help MATH MATH

Travis is filling a bathtub with water. He made a table showing the number of gallons of water in the bathtub based on the numbe

AleksAgata [21]

Lol another one?

So I looked at the graphs and the only one that actually even reaches 75 is the dotted one on the left. The one in the middle obviously doesn't go anywhere and the one on the right goes to 65, not 75.

6 0

3 years ago

Read 2 more answers

What’s the anwer I do not understand this

romanna [79]

Answer:

Step-by-step explanation:

So you have to get 2/3 of 128 grams which is about 85 grams. It says she has to mix 64 grams so she went over.

Hope this helps :)

8 0

3 years ago

TOP OF THE MORNIN TO THE PEOPLE THAT CAN ANSWER THIS!!!!

Dvinal [7]

surface area=4πr2=2700 cm2
r2=27004π=27004×3=225
r=225−−−√=15
volume=43πr3=43×3×153=13500 cm3

7 0

3 years ago

the telephone company purchased 95 yards of wire for $1235 in september. they plan on making a purchase of 285 yards in October.

Luden [163]

Ratio and propoertion

cost/amount is constant
1235/95=x/285
cross multiply or time both sides by (95 times 283)
351975=95x
divide oth sies by 95
3705=x

the cost is $3705

7 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:

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