*laughs* Sorry about that; for the most part, those can be ignored. That's my attempt to "show my work", and represents a compromise between furs who say "just give me the findings in plain language" and those who say "you can't just make claims like that... show us your statistics!" I feared that starting off the article explaining the rationale of t-tests and regression analyses would intimidate furries who just peeked in to read a short summary of what we learned (and who want to read something in plain English).
Greenreaper did a pretty good job explaining it =) Basically, if the p-value is "less than .05", it suggests that:
a) if it's a t-test, a difference between means of that magnitude would only be expected to be due to random error less than 5% of the time.
b) if it's a regression analyses, a linear relationship of that magnitude between two variables would only be expected to occur less than 5% of the time.
All of this needs to be taken with a grain of salt, of course. Statistics are based on assumptions and are inferences about reality based on a limited sample (Staghorne does a good job describing some of these concerns). That said, this IS how the vast majority of social science (and "hard science", for that matter) is analyzed!
*laughs* Sorry about that; for the most part, those can be ignored. That's my attempt to "show my work", and represents a compromise between furs who say "just give me the findings in plain language" and those who say "you can't just make claims like that... show us your statistics!" I feared that starting off the article explaining the rationale of t-tests and regression analyses would intimidate furries who just peeked in to read a short summary of what we learned (and who want to read something in plain English).
Greenreaper did a pretty good job explaining it =) Basically, if the p-value is "less than .05", it suggests that:
a) if it's a t-test, a difference between means of that magnitude would only be expected to be due to random error less than 5% of the time.
b) if it's a regression analyses, a linear relationship of that magnitude between two variables would only be expected to occur less than 5% of the time.
All of this needs to be taken with a grain of salt, of course. Statistics are based on assumptions and are inferences about reality based on a limited sample (Staghorne does a good job describing some of these concerns). That said, this IS how the vast majority of social science (and "hard science", for that matter) is analyzed!