70% of the U.S. population recycles. According to a green survey of a random sample of 250 college students, 204 said that they recycled. At alpha = 0.01, is there sufficient evidence to conclude that the proportion of college students who recycle is greater than 70%?

Respuesta :

Answer:

[tex]z=\frac{0.816 -0.7}{\sqrt{\frac{0.7(1-0.7)}{250}}}=4.002[/tex]  

[tex]p_v =P(z>4.002)=0.0000314[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.01[/tex] we have [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of people said that they recycled is significantly higher than 0.7 or 70%

Step-by-step explanation:

Data given and notation

n=250 represent the random sample taken

X=204 represent the people said that they recycled

[tex]\hat p=\frac{204}{250}=0.816[/tex] estimated proportion of people said that they recycled

[tex]p_o=0.7[/tex] is the value that we want to test

[tex]\alpha=0.01[/tex] represent the significance level

Confidence=99% or 0.99

z would represent the statistic (variable of interest)

[tex]p_v[/tex] 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 is higher than 0.7.:  

Null hypothesis:[tex]p\leq 0.7[/tex]  

Alternative hypothesis:[tex]p > 0.7[/tex]  

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

[tex]z=\frac{\hat p -p_o}{\sqrt{\frac{p_o (1-p_o)}{n}}}[/tex] (1)  

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

Calculate the statistic  

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

[tex]z=\frac{0.816 -0.7}{\sqrt{\frac{0.7(1-0.7)}{250}}}=4.002[/tex]  

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 [tex]\alpha=0.01[/tex]. The next step would be calculate the p value for this test.  

Since is a right tailed test the p value would be:  

[tex]p_v =P(z>4.002)=0.0000314[/tex]  

So the p value obtained was a very low value and using the significance level given [tex]\alpha=0.01[/tex] we have [tex]p_v<\alpha[/tex] so we can conclude that we have enough evidence to reject the null hypothesis, and we can said that at 1% of significance the proportion of people said that they recycled is significantly higher than 0.7 or 70%