99,26 €
110,29 €
-10% with code: EXTRA
Multiple Comparisons
99,26 € 
- We will send in 10–14 business days.
Multiple Comparisons demonstrates the most important methods of investigating differences between levels of an independent variable within an experimental design. The authors review the analysis of variance and hypothesis testing and describe the dimensions on which multiple comparisons vary. A feature is the use made of a famous experiment by Solomon Asch on group conformity. The authors demonstrate the statistical power of each method against this one experimental question.
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- Author: Alan J Klockars
- Publisher: SAGE Publications, Inc
- ISBN-10: 0803920512
- ISBN-13: 9780803920514
- Format: 22.5 x 14.6 x 0.6 cm, softcover
- Language: English
- SAVE -10% with code: EXTRA
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Multiple Comparisons demonstrates the most important methods of investigating differences between levels of an independent variable within an experimental design. The authors review the analysis of variance and hypothesis testing and describe the dimensions on which multiple comparisons vary. A feature is the use made of a famous experiment by Solomon Asch on group conformity. The authors demonstrate the statistical power of each method against this one experimental question.EXTRA 10 % discount with code: EXTRA
99,26 €
110,29 €
We will send in 10–14 business days.
The promotion ends in 15d.09:04:18
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Alan J Klockars
- Publisher: SAGE Publications, Inc
- ISBN-10: 0803920512
- ISBN-13: 9780803920514
- Format: 22.5 x 14.6 x 0.6 cm, softcover
- Language: English English
Multiple Comparisons demonstrates the most important methods of investigating differences between levels of an independent variable within an experimental design. The authors review the analysis of variance and hypothesis testing and describe the dimensions on which multiple comparisons vary. A feature is the use made of a famous experiment by Solomon Asch on group conformity. The authors demonstrate the statistical power of each method against this one experimental question.
Reviews