What statistical analysis should I use?

Number of Dependent Variables	Nature of Independent Variables	Nature of Dependent Variable(s)	Test(s)
1	0 IVs (1 population)	interval & normal	one-sample t-test	Stata
		ordinal or interval	one-sample median	Stata
		categorical  (2 categories)	binomial test	Stata
		categorical	Chi-square goodness-of-fit	Stata
	1 IV with 2 levels (independent groups)	interval & normal	2 independent sample t-test	Stata
		ordinal or interval
			Wilcoxon-Mann Whitney test	Stata
		categorical	Chi- square test	Stata
			Fisher's exact test	Stata
	1 IV with 2 or more levels (independent groups)	interval & normal	one-way ANOVA	Stata
		ordinal or interval	Kruskal Wallis	Stata
		categorical	Chi- square test	Stata
	1 IV with 2 levels (dependent/matched groups)	interval & normal	paired t-test	Stata
		ordinal or interval	Wilcoxon signed ranks test	Stata
		categorical	McNemar	Stata
	1 IV with 2 or more levels (dependent/matched groups)	interval & normal	one-way repeated measures ANOVA	Stata
		ordinal or interval	Friedman test	Stata
		categorical	repeated measures logistic regression	Stata
	2 or more IVs (independent groups)	interval & normal	factorial ANOVA	Stata
		ordinal or interval	ordered logistic regression	Stata
		categorical	factorial logistic regression	Stata
	1 interval IV	interval & normal	correlation	Stata
			simple linear regression	Stata
		ordinal or interval	non-parametric correlation	Stata
		categorical	simple logistic regression	Stata
	1 or more interval IVs and/or 1 or more categorical IVs	interval & normal	multiple regression	Stata
			analysis of covariance	Stata
		categorical	multiple logistic regression	Stata
			discriminant analysis	Stata
2 or more	1 IV with 2 or more levels (independent groups)	interval & normal	one-way MANOVA	Stata
2 or more	2 or more	interval & normal	multivariate multiple linear regression	Stata
2 sets of 2 or more	0	interval & normal	canonical correlation	Stata
2 or more	0	interval & normal	factor analysis	Stata
Number of Dependent Variables	Nature of Independent Variables	Nature of Dependent Variable(s)	Test(s)

Source: http://www.ats.ucla.edu/stat/stata/whatstat/
http://www.ats.ucla.edu/stat/stata/whatstat/whatstat.htm#1sampt


In statistics, Spearman's rank correlation coefficient or Spearman's rho, named after Charles Spearman and often denoted by the Greek letter  (rho) or as , is a nonparametric measure of statistical dependence between two variables. It assesses how well the relationship between two variables can be described using a monotonic function. If there are no repeated data values, a perfect Spearman correlation of +1 or −1 occurs when each of the variables is a perfect monotone function of the other.