The mother of a teenager has heard a claim that 29% of teenagers who drive and use a cell phone reported texting while driving. She thinks that this rate is too high and wants to test the hypothesis that fewer than 29% of these drivers have texted while driving. Her alternative hypothesis is that the percentage of teenagers who have texted when driving is less than 29%. Upper H 0 : p equals 0.29 Upper H Subscript a Baseline : p less than 0.29 She polls 40 randomly selected teenagers, and 5 of them report having texted while driving, a proportion of 0.125. The p-value is 0.011. Explain the meaning of the p-value in the context of this question.

The p value is a value in order to reject or not the null hypothesis. If the p value is higher than the significance level we FAIL to reject the null hypothesis otherwise we have enough evidence to reject the null hypothesis.

Step-by-step explanation:

Data given and notation

n=40 represent the random sample taken

X=5 represent the people report having texted while driving

estimated proportion of people report having texted while driving

is the value that we want to test

represent the significance level

z would represent the statistic (variable of interest)

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 less than 0.29.:  

Null hypothesis:  

Alternative hypothesis:  

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

(1)  

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

Calculate the statistic  

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

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 next step would be calculate the p value for this test.  

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

The p value is a value in order to reject or not the null hypothesis. If the p value is higher than the significance level we FAIL to reject the null hypothesis otherwise we have enough evidence to reject the null hypothesis.

3, 12, 48, 384, 1536, 6144, 24576, 98304

step-by-step explanation:

just keep timing it by 4.

-2 is the right