00:01
We're looking at secondary variants.
00:03
What kinds of validity does it impact? so for that, we need to look at the two types of validity in our experiments.
00:10
Internal and external.
00:13
So we'll start by defining these.
00:16
So internal validity is asking, does my study actually show a causal relationship here? so have i proven what i set out to prove? so did i find a causal relationship? is my study valid in itself? external validity is, can i apply this to other situations? can i generalise it? can i generalise my resort? so you might have an amazing study, but if you only performed it on a very small subset of a population, say college students, it might not have that external validity.
01:04
It might be great to looking at other college students, but mainly not the general population.
01:08
That would be high internal validity, low, so that's what we're looking at.
01:14
What is secondary variance? so we've got two variables of interest, the independent or the explanatory, and the dependent.
01:24
And we are looking at a relationship.
01:27
How does the independent affect the dependent? secondary variance refers to any third variable that might be impacting the relationship we see.
01:37
A confound.
01:39
So the confounding variable might impact both and it makes it look like there's a relationship between them when actually there isn't a direct relationship...
