| Essential Statistics For The Behavioral Sciences | 
enlarge | Author: Gary Heiman Publisher: Houghton Mifflin Company Category: Book
Buy New: $60.70
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Avg. Customer Rating: 1 reviews Sales Rank: 161252
Media: Hardcover Edition: 1 Number Of Items: 1 Pages: 302 Shipping Weight (lbs): 1.8 Dimensions (in): 10.1 x 8.3 x 0.7
ISBN: 0618252002 Dewey Decimal Number: 519.5 EAN: 9780618252008 ASIN: 0618252002
Publication Date: July 28, 2003 Availability: Usually ships in 1-2 business days Condition: Brand New. Delivery is usually 5 - 8 working days from order, International is by Royal Mail Airmail
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Product Description
This text uses the same conceptual, intuitive approach of Basic Statistics for the Behavioral Sciences, but eliminates extensive reference material and advanced or obscure statistical methods. Essentials presents only the procedures undergraduates need for reading research literature and conducting their own studies. New terms are integrated with more difficult concepts in an accessible, non-threatening format that provides concise explanations, creating a foundation and making further elaboration easier to understand. - A Quick Review sections revisit concepts, provide worked-out examples, and help students check comprehension through review questions.
- Computational formulas appear in color throughout each chapter and key terms are highlighted, reviewed in the chapter summary, and listed in a key terms section.
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| Customer Reviews:
focus on essentials April 13, 2008 1 out of 1 found this review helpful
Heiman offers a concise overview of what is useful in statistic, with an emphasis for the reader who is majoring in the behavioural sciences. There is no proving of theorems or lemmas, like there would be in a book for maths majors. Instead, the text starts at an elementary level, describing various types of graphs. Along with metrics like the mean, median and standard deviation. Hopefully, you've also encountered this in high school.
It goes more advanced from there. Always geared towards relevancy if you are designing an experiment. Often with human subjects. Hence there are issues of sampling from an underlying population. This should be a random sample, and there is an associated sampling error.
ANOVA and Chi square tests are covered. For many situations with multiple independent variables, these are very useful.
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