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DiKsa [7]
3 years ago
14

3000 is 32% of what number?

Mathematics
2 answers:
qwelly [4]3 years ago
8 0

   We have, 32% × x = 3000

   or, 32100 × x = 3000

   Multiplying both sides by 100 and dividing both sides by 32,

   we have x = 3000 × 10032

   x = 9375

   If you are using a calculator, simply enter 3000×100÷32, which will give you the answer.


Answer - 100,000

Andrej [43]3 years ago
7 0

Answer: 9375

Step-by-step explanation: 32/100 = 3000

x = 3000 x 100/32

x = 9375

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Yes. There is enough evidence to support the claim that the proportion of individuals who caught pertussis and were not up to date on their booster shot is higher than those that were.

P-value = 0.00013.

Step-by-step explanation:

This is a hypothesis test for the difference between proportions.

The claim is that the proportion of individuals who caught pertussis and were not up to date on their booster shot is higher than those that were.

Then, the null and alternative hypothesis are:

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

The significance level is 0.05.

The sample 1 (Group 1), of size n1=145 has a proportion of p1=0.124.

p_1=X_1/n_1=18/145=0.124

The sample 2 (Group 2), of size n2=355 has a proportion of p2=0.037.

p_2=X_2/n_2=13/355=0.037

The difference between proportions is (p1-p2)=0.088.

p_d=p_1-p_2=0.124-0.037=0.088

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

p=\dfrac{X_1+X_2}{n_1+n_2}=\dfrac{18+13.135}{145+355}=\dfrac{31}{500}=0.062

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{0.062*0.938}{145}+\dfrac{0.062*0.938}{355}}\\\\\\s_{p1-p2}=\sqrt{0+0}=\sqrt{0.001}=0.024

Then, we can calculate the z-statistic as:

z=\dfrac{p_d-(\pi_1-\pi_2)}{s_{p1-p2}}=\dfrac{0.088-0}{0.024}=\dfrac{0.088}{0.024}=3.68

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

\text{P-value}=P(z>3.68)=0.00013

As the P-value (0.00013) 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 proportion of individuals who caught pertussis and were not up to date on their booster shot is higher than those that were.

8 0
3 years ago
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