Hi, can you confirm or correct : so in the t test, when do you use the two sided
ID: 3250314 • Letter: H
Question
Hi, can you confirm or correct : so in the t test, when do you use the two sided por one sided p? Do you use the two sided table when testing two means? Also, when the p value is lower than the level of significance then we reject the null hypothesis? And when p value is higher than the level of significance we do not reject the null hypothesis? What about if it lies between the level of significance? Please shed some light Hi, can you confirm or correct : so in the t test, when do you use the two sided por one sided p? Do you use the two sided table when testing two means? Also, when the p value is lower than the level of significance then we reject the null hypothesis? And when p value is higher than the level of significance we do not reject the null hypothesis? What about if it lies between the level of significance? Please shed some lightExplanation / Answer
To your questions here are the comments:
when do you use the two sided por one sided p?
You use 2 sided p. Although both are given in the t tables. Just like the one in this link:
https://www2.palomar.edu/users/rmorrissette/Lectures/Stats/ttests/TTable.jpg
Do you use the two sided table when testing two means?
Not neccessarily. When equality is being tested between 2 means then you use 2 tailed, otherwise use 1 tailed.
Also, when the p value is lower than the level of significance then we reject the null hypothesis?
True. We say that if our p value is inside the rejection region then we reject null.
And when p value is higher than the level of significance we do not reject the null hypothesis?
True. Opposite as above point
What about if it lies between the level of significance?
If it lies between the level of significance then we say it is not in rejection region and hence we can't reject null hypothesis.
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.