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Bingel [31]
3 years ago
8

Solve for b -9 — + b = -1 3 B =

Mathematics
1 answer:
Rashid [163]3 years ago
5 0
Write it backwards to help. -9/3 - (-1) which equals -2. -2=B. I hope I helped! :)
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Answer:

x > 0

Step-by-step explanation:

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Amy is doing a science experiment on how a certain bacterium reacts to an antibiotic. She has 3 dishes of identical bacterium sa
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The sample size is 36 because 3x12=36
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A national manufacturer of ball bearings is experimenting with two different processes for producing precision ball bearings. It
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Answer:

A. As we are trying to test if the two processes yield different average errors, we are interested in any of the two posibilities: the average error of process A being statistically significant lower or bigger than the average error of Process B. That is why this is a two-tailed test.

B. t=-3.144

C. The critical value for a significance level of 0.05, a two tailed test with 4 degrees of freedom is t=±2.064.

D. P-value = 0.004

E. Reject H0

F. The probability of making a Type I error is equal to the significance level: P(Type I error) = 0.05.

Step-by-step explanation:

This is a hypothesis test for the difference between populations means.

The claim is that the two processes yield different average errors.

As we are trying to test if the two processes yield different average errors, we are interested in any of the two posibilities: the average error of process A being statistically significant lower or bigger than the average error of Process B. That is why this is a two-tailed test.

Then, the null and alternative hypothesis are:

H_0: \mu_1-\mu_2=0\\\\H_a:\mu_1-\mu_2\neq 0

being  μ1: average error for Process A and μ2: average error fo Process B.

The significance level is 0.05.

The sample 1, of size n1=12 has a mean of 2 and a standard deviation of 1.

The sample 1, of size n1=14 has a mean of 3 and a standard deviation of 0.5.

The difference between sample means is Md=-1.

M_d=M_1-M_2=2-3=-1

The estimated standard error of the difference between means is computed using the formula:

s_{M_d}=\sqrt{\dfrac{\sigma_1^2}{n_1}+\dfrac{\sigma_2^2}{n_2}}=\sqrt{\dfrac{1^2}{12}+\dfrac{0.5^2}{14}}\\\\\\s_{M_d}=\sqrt{0.083+0.018}=\sqrt{0.101}=0.318

Then, we can calculate the t-statistic as:

t=\dfrac{M_d-(\mu_1-\mu_2)}{s_{M_d}}=\dfrac{-1-0}{0.318}=\dfrac{-1}{0.318}=-3.144

The degrees of freedom for this test are:

df=n_1+n_2-1=12+14-2=24

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This test is a two-tailed test, with 24 degrees of freedom and t=-3.144, so the P-value for this test is calculated as (using a t-table):

P-value=2\cdot P(t

As the P-value (0.004) is smaller than the significance level (0.05), the effect is significant.

The null hypothesis is rejected.

There is  enough evidence to support the claim that the two processes yield different average errors.

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Step-by-step explanation:

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