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allsm [11]
3 years ago
8

Susie and Amelia solved the same equation using two separate methods. Their work is shown in the table below:

Mathematics
1 answer:
kvv77 [185]3 years ago
5 0
<span>Stephen and Aaron solved the same equation using two separate methods. Their work is shown in the table below:

Stephen Aaron:
3x - 2 = 5x - 6 3x - 2 = 5x - 6 
3x - 2 + 2 = 5x - 6 + 2 3x - 3x - 2 = 5x - 3x - 6
3x = 5x - 4 -2 = 2x - 6
3x - 5x = 5x - 5x - 4 -2 - 6 = 2x 
-2x = -4 -8 = 2x
x = 2 -4 = x

Identify who made the error and what he did wrong.
Aaron made the error when he subtracted 6.

Aaron made the error when he subtracted 3x.

Stephen made the error when he added 2.

Stephen made the error when he subtracted 5x.

answer:

</span>In the Aaron`s work:
- 2 = - 2 x - 6
and after that:
- 2 - 6 = 2 x
It should be:
- 2 + 6 = 2 x
or: - 2 + 6 = 2 x - 6 + 6
Answer:
A ) Aaron made the error when he subtracted 6.
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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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