This paper offers a practical guide to use null hypotheses significance testing and its alternatives. The focus is on improving the quality of statistical inference in quantitative communication research. More consistent reporting of descriptive statistics, estimates of effect size, confidence intervals around effect sizes, and increasing the statistical power of tests would lead to needed improvements over current practices. Alternatives including confidence intervals, effect tests, equivalence tests, and meta-analysis are discussed. © 2008 International Communication Association.