Statistical Power Analysis For The Behavioral Sciences
Condition: SECONDHAND
This is a secondhand book. The jacket image is a photograph of the exact copy we have in stock. This image shows the condition of this book. Further condition remarks are below.
Author: Jacob Cohen
Binding: Hardback
Published: Lawrence Erlbaum Associates, Publishers, 1988
Condition:
Book: Good
Jacket: N/A
Pages: Good
Markings: Previous owner
Condition remarks: Faded spine.
This essential academic text, "Statistical Power Analysis For The Behavioral Sciences," presents a comprehensive guide to the critical concepts of statistical power, effect size, and sample size determination. Jacob Cohen, a seminal figure in quantitative psychology, instructs researchers in the behavioral sciences on how to design studies with optimal statistical rigor. The work details the methods for calculating the probability of detecting an effect when one truly exists, offering invaluable insights for hypothesis testing and research planning. It serves as an indispensable resource for graduate students and seasoned academics seeking to enhance the validity and reliability of their empirical investigations.
Author: Jacob Cohen
Binding: Hardback
Published: Lawrence Erlbaum Associates, Publishers, 1988
Condition:
Book: Good
Jacket: N/A
Pages: Good
Markings: Previous owner
Condition remarks: Faded spine.
This essential academic text, "Statistical Power Analysis For The Behavioral Sciences," presents a comprehensive guide to the critical concepts of statistical power, effect size, and sample size determination. Jacob Cohen, a seminal figure in quantitative psychology, instructs researchers in the behavioral sciences on how to design studies with optimal statistical rigor. The work details the methods for calculating the probability of detecting an effect when one truly exists, offering invaluable insights for hypothesis testing and research planning. It serves as an indispensable resource for graduate students and seasoned academics seeking to enhance the validity and reliability of their empirical investigations.