Can anyone help with stats (using spss) for my psychology dissertation?

I'm exploring the relationships between three levels of gambling motivation, intrinsic, extrinsic and amotivation with loneliness and self-esteem. I've predicted that older people and females will be more lonelier than younger people and males. Also I'm predicting that younger gamblers will have lower self-esteem than older people. Any help for what test to use will be really useful. Thank you.

Can anyone help with stats (using spss) for my psychology dissertation?
I'm a little unclear if your "gambling motivation" variable is categorical. From what I can see, your set up looks like this:


If it's possible and you haven't done data collection yet, I would try splitting gambling motivation into two linear scales (intrinsic and extrinsic), probably Likert-type self-report measures unless you have something specific in mind.





IVs: Sex, Age, Gambling motivation(s)


DVs: Self esteem and Loneliness





You'll want to do an Analysis of Variance (ANOVA) in SPSS with each of your dependent variables.





Hope that helps!
Reply:Here are a few things that come to mind.





Obviously you will conduct bi-variate or zero-order correlations between all of your variables.





Secondly, according to your predictions there should be a positive correlation between age and self-esteem (as individuals get older their self-esteem also increases).





In order to investigate gender differences, you could simply conduct an independent sample t-test using gender as a factor and lonliness as the dependent variable.





In regards to age. The analysis of this variable partly depends upon how you have measured it. For example, if you measure age as a continuous variable (e.g. simply recording the age of each individual) then it limits the type of statistics that you can perform with it. If you have measured age as a categorical variable (e.g. everyone 18-24 is coded "1", everyone 24-34 is coded "2" and so on, then it would be possible to use this in an ANOVA. If you are wishing to do something like this you can still change your continuous age variable into a categorical variable, although you may have to justify why you chose these categories.





If you have a categorical variable for age, you could do a factorial anova with age and gender as the independent variables and loneliness as the dependent variable. This would allow you to examine the potential interaction between age and gender.
Reply:in general you should do this :





open spss then go to Analyze -%26gt; correlate -%26gt; bivariate





then add variables to the variables box





and choose person test if your data is (quantitative)





or sperman if your data is (qualitative)





then press OK








if the result showed you





correlation coefficient =0 (no relation)





correlation coefficient = +1 (strong relation and variable increased directly)





correlation coefficient = -1 (strong relation and variable increased reversely)