SPSS from two - to one tailed test If any of you would like to confirm if my understanding is correct or wrong, I will be most grateful.
I have done an independent-samples t-test (two-tailed),
for difference between women/men how they see their own skill sett.
In short: 
group women,n 76: mean 3,20 - std .980 
group men,n 21: mean 3,71 - std .956
df= 95
sig.level set to 0.05
t= - 2.150
sig. (2-tailed) 0.034
(critical value= -1.98 to 1.98)
statistics significant difference between men and women ...
I reject the null hypothesis.
I am going to find out the the results for a one-tailed 
test which SPSS do not check for. 
H0: There is no difference in drivingskills between women and men.
H1:Women have lower driving skills then men. 
I have understood that the principle is the same, but I have to  
first be clear on the direction, which is negative (group 2 have a higher mean).
Then I need to divide the significant in 2 which was -2.150/2=-1.075.
The area at 0.05 with 95 df one-tailed test in the "students distribution"
shows me about -1.661. 
I conclude therefore that I must accept the null hypothesis 
when doing a one-tailed test (since I have the number - 1,075)
Am I very lost here or have I understood it and done it correctly?
(She said with hope).
Thank you. 
 A: You should be dividing the $p$-value (0.034) by two, not the $t$-value. 
A: As the two-sided test splits the critical region in two halves, there will always be a mirror region on the side the data did not point towards. It is therefore more likely that a one-sided test will be significant than a two-sided tests (given that you are correct about the direction of the test). 
In practice, diviing the obtained p-value is the correct way to go, as the t-value does not change based on the directionality of the hypothesis.
Just some clarifications:
1) Be careful about your hypotheses:
The test is a test for difference of population MEANS.
"There is no difference in drivingskills between women and men." does not reflect this accurately. You could say: "The mean of the measure of driving skill is the same in the populations of men and women". Many textbooks are very lax in allowing all sorts of statements here, but the statistical test is solely testing the sense stated.
2) Be careful about the statement "accept the null hypothesis". While this was routinely used by Neyman and Pearson, many modern-day instructors teach not to use it and use "fail to reject H0" instead. Some reasons: The study might be underpowered, failure to show an effect does not directly allow statements about the vaildiity of hypotheses etc. 
