Publisher's Synopsis
The authors of this unique text found that while most students can "crunch" the numbers quite easily and accurately with a calculator or computer, many have trouble seeing the "big picture" or seeing how research questions and design influence data analysis. As a result, the authors developed a semantically consistent framework that integrates traditional research approaches (experimental, quasi-experimental, comparative) into three basic kinds of research questions (difference, associational, and descriptive), which, in turn, lead to three kinds or groups of statistics with the same names.
This text:
*helps students become good consumers of research by demonstrating how to analyze and evaluate research articles;
*offers a number of summarizing diagrams and tables that clarify confusing or difficult to learn topics;
*points out the value of qualitative research and how it should lead quantitative researchers to be more flexible;
*divides all quantitative research questions into five logically consistent categories that help students select appropriate statistics and understand their cause and effect; and
*classifies design into three major types: between groups, within subjects, and mixed groups and shows that, although these three types use the same general type of statistics (e.g., ANOVA), the specific statistics in between-groups design are different from those in within-subjects and mixed groups.
