Statistical Methods for Psychology

by David C . Howell (Author)

• Used

  Hardcover
  1996

  $3.23

  Intended for graduate-level courses in statistics for psychology majors, this best-seller has earned high marks among students and instructors for its clear, conceptual approach and strong emphasis on experimental psychology. The author presents statistics at an intuitive level to give students a sense of how tests work and how they interrelate. Stressing the value of data analysis before jumping in with a hypothesis test, Howell examines the connection between statistical tests and the theoretical questions posed by such experiments to develop students' conceptual skills.

• Used

  Paperback
  1992

  $3.23

• Used

  Hardcover
  1992

  $3.23

  This text highlights statistical methods useful for the behavioural sciences from a practitioner's perspective. The format and presentation of statistics should encourage students to research and analyze data. Students are exposed to the power and time-saving features of computer software with examples of output from Minitab, SPSS, BMDP, SAS, and others. Examples and exercises use real data to motivate students and show them the importance of statistical techniques in behavioural research. The edition has been improved by increasing computer coverage and integration, including graphical representations of computer output. Sections on probability, chi-square and multiple regression have been revised for greater clarity.

• New

  Paperback
  2006

  $76.52

  Statistical Methods for Psychology surveys the statistical techniques commonly used in the behavioral and social sciences, especially psychology and education. To help students gain a better understanding of the specific statistical hypothesis tests that are covered throughout the text, author David Howell emphasize conceptual understanding. Along with a significantly updated discussion of effect sizes and examples on how to write up the results of data analysis, this Sixth Edition continues to focus students on two key themes that are the cornerstones of this book's success: the importance of looking at the data before beginning a hypothesis test, and the importance of knowing the relationship between the statistical test in use and the theoretical questions being asked by the experiment.