Assume that you plan to use a significance level of alpha α equals =0.05 to test the claim that p1 equals = p2. use the given sample sizes and numbers of successes to find the pooled estimate p. round your answer to the nearest thousandth. n1 equals =100, n2 equals =100 x1 equals =42, x2 equals =45.

And we can use the following R code to find it: "2*pnorm(-0.428)"

The p value is a very high value and using any significance given always so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions are not significantly different.  

Step-by-step explanation:

1) Data given and notation  

people with some characteristic desired on sample 1

people with some characteristic desired on sample 2

sample selected 1

sample selected 2

represent the proportion estimated for 1

represent the proportion estimated for 2

represent the significance level

z would represent the statistic (variable of interest)  

represent the value for the test (variable of interest)  

2) Concepts and formulas to use  

We need to conduct a hypothesis in order to check if the proportion for the two samples are different , the system of hypothesis would be:  

Null hypothesis:  

Alternative hypothesis:  

We need to apply a z test to compare proportions, and the statistic is given by:  

  (1)  

3) Calculate the statistic  

Replacing in formula (1) the values obtained we got this:  

4) Statistical decision

We can calculate the p value for this test.    

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

And we can use the following R code to find it: "2*pnorm(-0.428)"

The p value is a very high value and using any significance given always so we can conclude that we have enough evidence to FAIL to reject the null hypothesis, and we can say the two proportions are not significantly different.  

the answer is 5/3x+7/5y+7

answer: the answer is 35%