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bulgar [2K]
4 years ago
5

How do you turn 0.875 into a fraction

Mathematics
1 answer:
galina1969 [7]4 years ago
6 0

Answer: 5/8

Step-by-step explanation:

0.875 is equal to 875/1000 because there are 3 decimal places, which is the amount of zeroes after the 1 as i like to think of it, and then to simplify it

875/1000 = 35/40 = 5/8

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Which pair of expressions is equivalent? 2(x + 5) and 2x + 10 B. 3x – 6 + 4x + 9 and 7x + 15 0. C. 4y - 2) and 4y - 2 0 D. 5y +
kari74 [83]

Answer:

A

Step-by-step explanation:

the equivalent pair of expression are 2(x+5)and 2x+10

7 0
3 years ago
Find the sum and express it in simplest form.<br> (-73-y + 1) + (-7y3 - 6y)
meriva

Answer:

-(7y^3+7y+36)

Step-by-step explanation:

(-73-y+1)+(-7y^3-6y)

-37+1-y-7y^3-6y

-36-y-6y-7y^3

-36-7y-7y^3

-7y^3-7y-36

-(7y^3+7y+36)

3 0
3 years ago
HELP HELP HELP HELP HELP HELP<br> PLEASE
Brilliant_brown [7]

Answer: 1 \frac{5}{27}

Step-by-step explanation:

\frac{8}{9}  x  1\frac{1}{3} = 1\frac{5}{27}

3 0
3 years ago
Read 2 more answers
Researchers at the National Cancer Institute released the results of a study that investigated the effect of weed-killing herbic
jolli1 [7]

Answer:

The 95% confidence interval for the difference in the proportion of cancer diagnoses between the two groups is (0.3834, 0.5166).

Step-by-step explanation:

Before building the confidence interval, we need to understand the central limit theorem and subtraction between normal variables.

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 between normal variables:

When two normal variables are subtracted, the mean is the difference of the means, while the standard deviation is the square root of the sum of the variances.

The randomly sampled 400 dogs from homes where an herbicide was used on a regular basis, diagnosing lymphoma in 230 of them.

This means that:

p_h = \frac{230}{400} = 0.575, s_h = \sqrt{\frac{0.575*0.425}{400}} = 0.0247

Of 200 dogs randomly sampled from homes where no herbicides were used, only 25 were found to have lymphoma.

This means that:

p_n = \frac{25}{200} = 0.125, s_n = \sqrt{\frac{0.125*0.875}{200}} = 0.0234

Distribution of the difference:

p = p_h - p_n = 0.575 - 0.125 = 0.45

s = \sqrt{s_h^2+s_n^2} = \sqrt{0.0247^2 + 0.0234^2} = 0.034

Confidence interval:

The confidence interval is:

p \pm zs

In which

z is the zscore that has a pvalue of 1 - \frac{\alpha}{2}.

95% confidence level

So \alpha = 0.05, z is the value of Z that has a pvalue of 1 - \frac{0.05}{2} = 0.975, so Z = 1.96.

The lower bound is 0.45 - 1.96(0.034) = 0.3834

The upper bound is 0.45 + 1.96(0.034) = 0.5166

The 95% confidence interval for the difference in the proportion of cancer diagnoses between the two groups is (0.3834, 0.5166).

3 0
3 years ago
Order 3, -4,7,-1 and -6 from least to greatest
katrin [286]
-6, -4, -1, 3, 7

Hope this helps!
5 0
3 years ago
Read 2 more answers
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