- #1
prelic
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Hey all,
2 quick questions:
1. When dealing with the difference between 2 population means (independent samples) or differences of paired data (dependent), a lot of the questions are similar to: "is there sufficient evidence to prove that the difference is 0" or "is there enough evidence to prove that X is sufficiently different from Y", etc. My question is, is there any difference between finding the P-values/z-score and finding and interpreting the confidence interval?
For example,
[tex]\bar{x}=23.87[/tex]
[tex]\bar{y}=27.34[/tex]
[tex]S_1=11.6[/tex]
[tex]S_2=8.85[/tex]
[tex]m=79[/tex]
[tex]n=85[/tex]
[tex]\alpha=.05[/tex]
Q: Reject or fail to reject:
[tex]H_0:\mu_1-\mu_2=0[/tex]
[tex]H_a:\mu_1-\mu_2\neq0[/tex]
Using P-values:
[tex]z=-2.14, P=2*(1-\Phi(2.14))=.016[/tex], and [tex]2*.016 = .032 < .05 [/tex] so REJECT
Using Confidence Intervals:
[tex]z_{\alpha/2}=1.96[/tex]
CI:[tex]\bar{x}-\bar{y} \pm 1.96*(1.62)[/tex]
[tex]=(-6.645,-.2948)[/tex]
Because 0 is not contained in the confidence interval, we reject the hypothesis that [tex]\mu_1-\mu_2=0[/tex]
Is there any difference between these two calculations and the conclusions I arrived at? When presented these kinds of problems, can I pick either method and arrive at the same answer?
And my other quick question is, when calculating a CI, you will arrive at the same conclusions (different signs, same numbers) when calculating [tex]\mu_1-\mu_2[/tex] as [tex]\mu_2-\mu_1[/tex], right? How would you interpret a confidence interval such as (30,-5)? To me this interval doesn't make sense.
Thanks!
2 quick questions:
1. When dealing with the difference between 2 population means (independent samples) or differences of paired data (dependent), a lot of the questions are similar to: "is there sufficient evidence to prove that the difference is 0" or "is there enough evidence to prove that X is sufficiently different from Y", etc. My question is, is there any difference between finding the P-values/z-score and finding and interpreting the confidence interval?
For example,
[tex]\bar{x}=23.87[/tex]
[tex]\bar{y}=27.34[/tex]
[tex]S_1=11.6[/tex]
[tex]S_2=8.85[/tex]
[tex]m=79[/tex]
[tex]n=85[/tex]
[tex]\alpha=.05[/tex]
Q: Reject or fail to reject:
[tex]H_0:\mu_1-\mu_2=0[/tex]
[tex]H_a:\mu_1-\mu_2\neq0[/tex]
Using P-values:
[tex]z=-2.14, P=2*(1-\Phi(2.14))=.016[/tex], and [tex]2*.016 = .032 < .05 [/tex] so REJECT
Using Confidence Intervals:
[tex]z_{\alpha/2}=1.96[/tex]
CI:[tex]\bar{x}-\bar{y} \pm 1.96*(1.62)[/tex]
[tex]=(-6.645,-.2948)[/tex]
Because 0 is not contained in the confidence interval, we reject the hypothesis that [tex]\mu_1-\mu_2=0[/tex]
Is there any difference between these two calculations and the conclusions I arrived at? When presented these kinds of problems, can I pick either method and arrive at the same answer?
And my other quick question is, when calculating a CI, you will arrive at the same conclusions (different signs, same numbers) when calculating [tex]\mu_1-\mu_2[/tex] as [tex]\mu_2-\mu_1[/tex], right? How would you interpret a confidence interval such as (30,-5)? To me this interval doesn't make sense.
Thanks!
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