ISBN13: | 9781483347462 |
ISBN10: | 148334746X |
Kötéstípus: | Keménykötés |
Lásd még | 9781483350851 |
Terjedelem: | oldal |
Méret: | 0x0x0 mm |
Nyelv: | angol |
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BUNDLE: Privitera: Statistics for the Behavioral Sciences + Hettich: Your Undergraduate Degree in Psychology
GBP 84.00
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Hettich: Your Undergraduate Degree in Psychology
Innovative strategies for psychology majors to survive and thrive in the workforce
Nearly 100,000 students graduate each year with a bachelor’s degree in psychology, and a majority of these students will enter the workforce instead of pursuing a graduate degree. Many will find themselves tentatively deciding their next steps amid a complex and changing economic and job environment.
In this text, authors and professors Paul I. Hettich and R. Eric Landrum provide innovative strategies and tools for succeeding after college with an undergraduate degree in psychology. Drawing on current research data, applied theory, and both academic and workplace experiences, they help stimulate self-reflection and improve decision making as students approach their careers. The text covers key topics in the college-to-career transition, including career planning and development, identifying and transferring marketable skills, building and sustaining strong networks, understanding what employers want and don’t want, coping with personal life changes, becoming a valued employee, and more.
Privitera: Statistics for the Behavioral Sciences
Take a tour of the book
This engaging text connects statistics to science using current research and real-life examples relevant to students lives.
Statistics for the Behavioral Sciences is an introduction to statistics text that will engage students in an ongoing spirit of discovery by illustrating how statistics apply to modern-day research problems. By integrating instructions, screenshots, and practical examples for using IBM SPSS® Statistics software, the book makes it easy for students to learn statistical concepts within each chapter. Gregory J. Privitera takes a user-friendly approach while balancing statistical theory, computation, and application with the technical instruction needed for students to succeed in the modern era of data collection, analysis, and statistical interpretation.
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