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Zolol [24]
3 years ago
5

-4b-5+2b=10 Help me solve this. I'm thinking way to hard.

Mathematics
1 answer:
enot [183]3 years ago
8 0
Isolate the variables. You want to get the five on the same side as the ten, so, you add  five to both sides.

-4b+2b=15

-2b=15
b= -7.5

I believe. You may want to double check my work though.
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Ms. Barclay ordered 9 cupcakes.

Step-by-step explanation:

$1.25x9=11.25

11.25+3.25=$14.50

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Is 63.90 greater than 63.990
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Maelin raised $50 plus $3 for each mile, m, that she walked in a fund-raiser walk. Which expression represents the situation? Ch
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An insurance company selected a random sample of 500 clients under 18 years of age and found that 180 of them had had an acciden
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Answer:

a) The pooled proportion is p=0.3.

b) P-value = 0.000078

c) Lower bound = 0.0556

d) Upper bound = 0.1644

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

The claim is that the accident proportions differ between the two age groups .

Then, the null and alternative hypothesis are:

H_0: \pi_1-\pi_2=0\\\\H_a:\pi_1-\pi_2\neq 0

The significance level is 0.05.

The sample 1, of size n1=500 has a proportion of p1=0.36.

p_1=X_1/n_1=180/500=0.36

The sample 2, of size n2=600 has a proportion of p2=0.25.

p_1=X_1/n_1=150/600=0.25.

The difference between proportions is (p1-p2)=0.11.

p_d=p_1-p_2=0.36-0.25=0.11

The pooled proportion, needed to calculate the standard error, is:

p=\dfrac{X_1+X_2}{n_1+n_2}=\dfrac{180+150}{500+600}=\dfrac{330}{1100}=0.3

The standard error for the difference between proportions can now be calculated as:

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

s_{p1-p2}=\sqrt{\dfrac{p(1-p)}{n_1}+\dfrac{p(1-p)}{n_2}}=\sqrt{\dfrac{0.3*0.7}{500}+\dfrac{0.3*0.7}{600}}\\\\\\s_{p1-p2}=\sqrt{0.00042+0.00035}=\sqrt{0.00077}=0.0277

Then, we can calculate the z-statistic as:

z=\dfrac{p_d-(\pi_1-\pi_2)}{s_{p1-p2}}=\dfrac{0.11-0}{0.0277}=\dfrac{0.11}{0.0277}=3.964

This test is a two-tailed test, so the P-value for this test is calculated as (using a z-table):

P-value=2\cdot P(t>3.964)=0.000078

As the P-value (0.000078) 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 accident proportions differ between the two age groups.

If we want to calculate the bounds of a 95% confidence interval, we start by calculating the margin of error.

For a 95% CI, the critical value for z is z=1.96.

Then, the margin of error is:

MOE=z \cdot s_{p1-p2}=1.96\cdot 0.0277=0.0544

Then, the lower and upper bounds of the confidence interval are:

LL=(p_1-p_2)-z\cdot s_{p1-p2} = 0.11-0.0544=0.05561\\\\UL=(p_1-p_2)+z\cdot s_{p1-p2}= 0.11+0.0544=0.16439

The  95% confidence interval for the population mean is (0.0556, 0.1644).

5 0
3 years ago
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