
Sách keo gáy, bìa mềm
Many researchers jump from data collection directly
into testing hypothesis without realizing these tests can go profoundly
wrong without clean data. This book provides a clear, accessible,
step-by-step process of important best practices in preparing for data
collection, testing assumptions, and examining and cleaning data in
order to decrease error rates and increase both the power and
replicability of results.
Jason W. Osborne, author of the handbook Best Practices in Quantitative Methods (SAGE,
2008) provides easily-implemented suggestions that are evidence-based
and will motivate change in practice by empirically demonstrating―for
each topic―the benefits of following best practices and the potential
consequences of not following these guidelines.
Thể loại:Mathematics
Mathematics - Mathematical Statistics
Năm:2012
Ngôn ngữ:english
Trang:296