8+30\2+4=27 put parentheses so it can equal 23 and 13

The measure of EFH is twice the measure of GFH. What is the

Vladimir [108]

Answer:

30° = m∠GFH

Step-by-step explanation:

Since ∠EFH and ∠GFH are complementary, the sum of their measures i 90.

Let x = m∠GFH

2x = m∠EFH

m∠GFH + m∠EFH = 90

x + 2x = 90

3x = 90

x = 30° = m∠GFH

8 0

3 years ago

What is the prime factorization of 33

schepotkina [342]

The answer is 11 and 3

4 0

3 years ago

The lines below are parallel. If the slope of the green line is -2, what is the slope of the redline?

scoray [572]

D. -2, if the lines are parallel then the slope is the same but the y-int is different

3 0

2 years ago

What is the rectangle area

pentagon [3]

Length times the width

3 0

3 years ago

Read 2 more answers

According to an article in Newsweek, the natural ratio of girls to boys is 100:105. In China, the birth ratio is 100:114 (46.7%

mojhsa [17]

Answer:

$z=\frac{0.42 -0.467}{\sqrt{\frac{0.467(1-0.467)}{150}}}=-1.154$

$p_v =2*P(z$

So the p value obtained was a very high value and using the significance level given $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of girls born is not significantly different from 0.467

Step-by-step explanation:

Data given and notation

n=150 represent the random sample taken

X=63 represent the number of girls born

$\hat p=\frac{63}{150}=0.42$ estimated proportion of girls born

$p_o=0.467$ is the value that we want to test

$\alpha=0.05$ represent the significance level

Confidence=95% or 0.95

z would represent the statistic (variable of interest)

$p_v$ represent the p value (variable of interest)

Concepts and formulas to use

We need to conduct a hypothesis in order to test the claim that the true proportion if girls is 0.467.:

Null hypothesis: $p=0.467$

Alternative hypothesis: $p \neq 0.467$

When we conduct a proportion test we need to use the z statistic, and the is given by:

$z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}$ (1)

The One-Sample Proportion Test is used to assess whether a population proportion $\hat p$ is significantly different from a hypothesized value $p_o$ .

Calculate the statistic

Since we have all the info requires we can replace in formula (1) like this:

$z=\frac{0.42 -0.467}{\sqrt{\frac{0.467(1-0.467)}{150}}}=-1.154$

Statistical decision

It's important to refresh the p value method or p value approach . "This method is about determining "likely" or "unlikely" by determining the probability assuming the null hypothesis were true of observing a more extreme test statistic in the direction of the alternative hypothesis than the one observed". Or in other words is just a method to have an statistical decision to fail to reject or reject the null hypothesis.

The significance level provided $\alpha=0.05$ . The next step would be calculate the p value for this test.

Since is a bilateral test the p value would be:

$p_v =2*P(z$

So the p value obtained was a very high value and using the significance level given $\alpha=0.05$ we have $p_v>\alpha$ so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can said that at 5% of significance the proportion of girls born is not significantly different from 0.467

3 0

3 years ago