How do you report a Mann–Whitney test? I am doing my dissertation, and I am conducting a number of tests. After using a Kruskal–Wallis test, I usually report the result like this: 

There is a significant difference $(\chi^2_{(2)}=7.448, p=.024)$ between the means of...

But now I conducted a Mann–Whitney test, and I am not sure which values to present. SPSS gives me a Mann–Whitney $U$, Wilcoxon $W$, $Z$ and $P$-value. Do I present all these 4 values? Or are some irrelevant?
 A: Wikipedia appears to have your answers. Here's an excerpt from the example statement of results:

In reporting the results of a Mann–Whitney test, it is important to state:
  
  
*
  
*A measure of the central tendencies of the two groups (means or medians; since the Mann–Whitney is an ordinal test, medians are usually recommended)
  
*The value of U
  
*The sample sizes
  
*The significance level.
  
  
  In practice some of this information may already have been supplied and common sense should be used in deciding whether to repeat it. A typical report might run,
"Median latencies in groups E and C were 153 and 247 ms; the distributions in the two groups differed significantly (Mann–Whitney U = 10.5, n1 = n2 = 8, P < 0.05 two-tailed)."

The Wilcoxon signed-rank test is appropriate for paired samples, whereas the Mann–Whitney test assumes independent samples. However, according to Field (2000), the Wilcoxon $W$ in your SPSS output is "a different
version of this statistic, which can be converted into a Z score and can, therefore, be compared against critical values of the normal distribution." That explains your $z$ score too then!
FYI, Wikipedia adds that, for large samples, $U$ is approximately normally distributed.  Given all these values, one can also calculate the effect size $η^2$, which in the case of Wikipedia's example is 0.319 (a calculator is implemented in section 11 here).  However, this transformation of the test statistic depends on the approximate normality of $U$, so it might be inaccurate with ns = 8 (Fritz et al., 2012).
P.S. The Kruskal–Wallis test's results should not be interpreted as revealing differences between means except under special circumstances. See @Glen_b's answer to another question, "Difference Between ANOVA and Kruskal-Wallis test" for details.
References
Field, A. (2000). 3.1. Mann-Whitney test. Research Methods 1: SPSS for Windows part 3: Nonparametric tests. Retrieved from http://www.statisticshell.com/docs/nonparametric.pdf.
Fritz, C. O., Morris, P. E., & Richler, J. J. (2012). Effect size estimates: current use, calculations, and interpretation. Journal of Experimental Psychology: General, 141(1), 2–18.  PDF available via ResearchGate.
