i really am desperate for help with this, since I have to present my results at a conference in less than two weeks. I am a statistics-noob undergraduate psychoglogy-student, so please go easy on me.

Research and Variables

I want to examine the correlative relationship between a personality trait (

**PT**) and spatial memory (

**SM**). My hypothesis is, that there is a relevant, positive correlation between these two. However, here are all the important variables:

- Spatial Memory (
**SM**): The outcome, scaled measure - Personality Trait (
**PT**): The predictor, scaled measure - Intelligence (
**IQ**): As a possible covariate, scaled measure - Subjects Age (
**AGE**): As a possible covariate, scaled measure - PC-Skills (
**PC**): As a possible covariate, scaled measure - Several other variables, also possible covariates, won't list them all here

Sample & Data-analysis so far

Unfortunately my sample-size is very limited (

*N = 26*), which causes a lot of problems. This is due to the special nature of my population and there's nothing I can do about it now, except for making the best of it.

I cannot make any assumptions about normal distribution in the population, since my data is not sufficient. So let's say there's no normal distribution. However, I will be using some methods that require normally distributed data, like the pearson correlation anyway, since I've been told that the issue can be ignored. If I'm completely wrong about this, let me know.

Correlations with the outcome:

- r (
**PT**,**SM**) ~ .49* - r (
**IQ**,**SM**) ~ -.40* - r (
**AGE**,**SM**) ~ .70** - r (
**PC**,**SM**) ~ -.21 (*not significant*) - the other correlations were not significant either, so that's why I didn't list them

**Now to my problem(s):**

- I want to make sure that the influence on SM comes from
**PT**and not**PT**in interaction with the other covariates. I would use a mutiple regression for this, but I'm not sure if I'm supposed to, due to my small sample size, etc. A LOESS-curve shows a linear connection. The predictor does show small, insignificant correlations to the other variables, as r (**AGE**,**PT**) ~ .24 (*not significant*).

Questions:

- Can I run a multiple Regression on this?
- If yes: Do I only include the correlations between the outcome
**SM**and the variables which turn out to be significant, or do I use all variables (which wouldn't work due to my small sample size, right?) - If yes: Do i use the ENTER-Method?
- If no: What else can I do to isolate the effect of
**PT**?

I hope I didn't forget anything.. Sorry in that case. Would be extremely thankful if anyone can help me with this!!