SOLUTION: In a program designed to help patients stop​ smoking, 156 patients were given sustained​ care, and 84.1​% of them were no longer smoking after one month. Use a 0.01 significa

Algebra ->  Probability-and-statistics -> SOLUTION: In a program designed to help patients stop​ smoking, 156 patients were given sustained​ care, and 84.1​% of them were no longer smoking after one month. Use a 0.01 significa      Log On


   



Question 1156754: In a program designed to help patients stop​ smoking, 156 patients were given sustained​ care, and 84.1​% of them were no longer smoking after one month. Use a 0.01 significance level to test the claim that 80​% of patients stop smoking when given sustained care. I have solved the test statistic and it is correct but I just need the p- value for the hypothesis test. Thanks in advance!
Upper H 0​: p equals 0.8
Upper H 1​: p not equals 0.8
The test statistic is 1.28.
The p value for this hypothesis is ?

Answer by jim_thompson5910(35256) About Me  (Show Source):
You can put this solution on YOUR website!

z = (phat - p)/(sqrt(p*(1-p)/n))
z = (0.841 - 0.8)/(sqrt(0.8*(1-0.8)/156))
z = 1.28022458967168
z = 1.28 is the test statistic
Nice job on getting the correct test statistic

Now use a Z table found in the back of your stats textbook to find the area under the standard normal distribution.
If you do not have a book with you, then you can use a Z table such as this one
https://www.ztable.net/
To find that
P(Z < 1.28) = 0.89973
note how I've highlighted the proper row and column which represent 1.20 and 0.08 combining to 1.28


So,
P(Z > 1.28) = 1-P(Z < 1.28)
P(Z > 1.28) = 1-0.89973
P(Z > 1.28) = 0.10027 approximately

Due to the "not equal" sign in the alternative hypothesis, we have a two tailed test. This means we will double the result to get the area in both tails.

2*0.10027 = 0.20054

The p value is approximately 0.20054


Extra Info:
At the significance level alpha = 0.01, we fail to reject the null. We can only reject the null if the p value is smaller than alpha. Failing to reject the null means we effectively "accept" the null hypothesis (until other data comes along to invalidate it). In other words, we conclude that p = 0.8 is the case. In the context of the problem, we conclude that 80% of patients quit smoking after one month.