# Two-sample pooled t-test for difference of population means

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```					Two-sample pooled t-test for difference of population means
Why?        To compare two unknown population means, 1 and 2.

When?       The following conditions must be present for the test to be accurate and valid. All of
the conditions may have to be assumed to proceed with the test.
1. 1 and 2 are unknown but assumed to be equal.
2. The samples are selected randomly.
3. The samples are selected independently.
4. The samples are from normally distributed populations.
How:
Preliminary: • Select the level of significance,  (use 0.05 unless otherwise stated).
• Define 1 and 2 in the context of the problem.
1. State the null hypothesis: H0: 1 = 2

Choose an alternative hypothesis from one of the following:
(i.) H1: 1 > 2            (ii.) H1: 1 < 2           (iii.) H1: 1  2

2. Calculate the test statistic:
n1  1s12  n2  1s 22
First find the pooled standard deviation s p                                        ,
n1  n2  2
then calculate the test statistic

t0 
x1  x2 
1  1 
sp   
n n 
 1  2 

3. Find the P-value (observed significance level): using a t distribution with
n1  n2  2 degrees of freedom; each case corresponds to the alternative hypotheses
listed above.
(i.) P  Pt  t 0          (ii.) P  Pt  t 0           (iii.) P  2 Pt | t 0 |

t0                    t0                                | t0 |          | t0 |

4. Conclusion: Reject H0 if the P-value is less than the level of significance; otherwise, do
not reject H0. Write a conclusion in statistical terms as well as a practical conclusion in
the context of the problem. The practical conclusion should always be stated in terms of
the alternative hypothesis. When H0 is rejected the result is “statistically significant.”

Two-sample pooled t-interval for 1-2
Why?        To estimate the difference between two population means 1 - 2.
When?       Under the same conditions as for the t-test listed above.
How:
1      1 
x1  x2   t c s p
  
n n 
 1      2 

where t c is the critical value from a t-distribution with n1  n2  2 degrees of freedom (df) and
corresponding to level C confidence..

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 views: 29 posted: 12/11/2011 language: English pages: 1
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