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iVinArrow [24]
3 years ago
8

How would I solve this ? Steps ?

Mathematics
2 answers:
Oxana [17]3 years ago
3 0
The answer would by -9 since you subtracted 9 from 5 which decreased the value of y.
stepan [7]3 years ago
3 0
"the answer would be -9 since you subtracted 9 from 5 which decreased the value of y."

how is it negative 9 if you were to subtract 9 - 5 it would be 4
and if you were to subtract 5 - 9 it would be negative 4 
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+ 2x + 12y + 4<br><br> What are the coefficients of this expression?
Tanzania [10]

Answer:

The coefficients are: 2, 12, 4.

Step-by-step explanation:

7 0
3 years ago
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A box is x to inches high,(2x+3)inches wide, and (2x+5) of inches long. In terms of x, what is the volume (v) of the box?
Advocard [28]

Answer:

The volume of the box is V=(4x^3+16x^2+15x)\ in^3

Step-by-step explanation:

we know that

The volume of the box is equal to

V=LWH

where

L is the length of the box in inches

W is the width of the box in inches

H is the height of the box in inches

we have

L=(2x+5)\ in\\W=(2x+3)\ in\\H=x\ in

substitute in the formula

V=(2x+5)(2x+3)x

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V=(4x^2+16x+15)(x)

V=(4x^3+16x^2+15x)\ in^3

6 0
3 years ago
Consider the following hypothesis test: H0: μ1 - μ2 = 0 Ha: μ1 - μ2 ≠ 0 There are two independent samples taken from the two pop
nlexa [21]

Answer:

The value of the test statistic is z = 1.78

Step-by-step explanation:

Before finding the test statistic, we need to understand the central limit theorem and subtraction of normal variables.

Central Limit Theorem

The Central Limit Theorem establishes 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.

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.

Sample 1:

\mu_1 = 110, s_1 = \frac{7.2}{\sqrt{81}} = 0.8

Sample 2:

\mu_2 = 108, s_2 = \frac{6.3}{\sqrt{64}} = 0.7875

The test statistic is:

z = \frac{X - \mu}{s}

In which X is the sample mean, \mu is the value tested at the null hypothesis, and s is the standard error.

0 is tested at the null hypothesis:

This means that \mu = 0

Distribution of the difference:

X = \mu_1 - \mu_2 = 110 - 108 = 2

s = \sqrt{s_1^2+s_2^2} = \sqrt{0.8^2+0.7875^2} = 1.1226

What is the value of the test statistic?

z = \frac{X - \mu}{s}

z = \frac{2 - 0}{1.1226}

z = 1.78

The value of the test statistic is z = 1.78

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3 years ago
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qaws [65]

Answer:

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