This paper is a summary of the doctoral thesis by the same name. The thesis set out to gain a better understanding of the differences between human translation and the post-editing of statistical machine translation for general text types for the English-Dutch language pair. Three aspects were taken into account (translation process, translation quality, and translator attitude) for two participant groups (professional translators and student translators). A translation quality assessment approach was developed to study the product, and keystroke logging and eye tracking tools were used to study the process. This summary addresses the research questions and key findings of the thesis, alongside practical and methodological implications of the work. Overall, post-editing was found to be faster than regular human translation, while being cognitively less demanding and leading to products of comparable quality. Students produced texts of comparable quality to professional translators, although they struggled with adequacy issues, and their process data suggests a lack of efficiency. Post-editing effort is influenced by different types of machine translation errors, in particular by coherence issues, meaning shifts, grammatical, and structural issues.