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3 years ago

WHICH EXPRESSION HAS THE SAME VALUE AS 8-(-4)?

Mathematics

2 answers:

s344n2d4d5 [400]3 years ago

8 0

8 - (-4) [2 negatives become a positive]

8 + 4 = 12

A.) - 8 + 4 = -4

B.) -8 + (-4) = -12

C.) 8 + (-4) = 4

D.) 4 - (-8) = 4 + 8 = 12

Your answer is D

Yuri [45]3 years ago

5 0

It’s D because

8-(-4)=
8+4=
=12

A) -8+4= -4
B) -8+(-4)= -12
C) 8+(-4)= 4
D) 4-(-8)= 12

So it’s D

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A certain change in a process for manufacturing component parts is being considered. Samples are taken under both the existing a

mr_godi [17]

Answer:

And the 90% confidence interval for the difference would be given by:(-0.022;0.0017).

Step-by-step explanation:

Previous concepts

A confidence interval is "a range of values that’s likely to include a population value with a certain degree of confidence. It is often expressed a % whereby a population means lies between an upper and lower interval".

The margin of error is the range of values below and above the sample statistic in a confidence interval.

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

$p_A$ represent the real population proportion for brand A

$\hat p_A =\frac{80}{2000}=0.04$ represent the estimated proportion for the new process

$n_A=2000$ is the sample size required for Brand A

$p_B$ represent the real population proportion for brand b

$\hat p_B =\frac{75}{1500}=0.05$ represent the estimated proportion for the before process

$n_B=1500$ is the sample size required for before process

$z$ represent the critical value for the margin of error

The population proportion have the following distribution

$p \sim N(p,\sqrt{\frac{p(1-p)}{n}})$

The confidence interval for the difference of two proportions would be given by this formula

$(\hat p_A -\hat p_B) \pm z_{\alpha/2} \sqrt{\frac{\hat p_A(1-\hat p_A)}{n_A} +\frac{\hat p_B (1-\hat p_B)}{n_B}}$

For the 90% confidence interval the value of $\alpha=1-0.90=0.1$ and $\alpha/2=0.05$ , with that value we can find the quantile required for the interval in the normal standard distribution.