This thesis examines the retrieval effectiveness of two Web search engines. The two search engines are chosen to represent two different types Google as a broad general search engine and Dogpile as a broad general metasearcher. Twenty queries have been used and the first twenty hits for each query were evaluated for relevance. The queries were invented by the authors, based upon their interests and information needs. They were expressed in a general manner, by using one or several keywords, in accordance with the simple search mode available for each search engine. The measure used is precision, and two different methods of measuring precision are used to give credit to those search engines that present relevant hits early in their ranked lists. Due to the subjective character of the concept of relevance and in order to avoid bias in the study, our criteria for evaluating the retrieved documents were designed to be as thorough and detailed as possible. A binary relevance scale was used where relevant documents and mirror links were assigned the value 1 and irrelevant documents, dead links, and duplicate links were assigned the value 0. The results show that Google is the best performing search engine of these two. Although Google is the overall winner, the differences between the two are minimal and both Google and Dogpile are highly effective search engines, when using one or more keywords to express your information need in the simple search mode, i.e. default setting.