Using Factorial Anova In Spss To Investigate The Combined Effect Of Neo Retro Package Style And Brand Establishment Date On Consumer Attitudes
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Using Factorial ANOVA in SPSS to Investigate the Combined Effect of Neo-retro Package Style and Brand Establishment Date on Consumer Attitudes
This case study describes how to run factorial analysis of variance (ANOVA) using IBM SPSS Statistics to examine the combined impact of packaging style and date of brand establishment on consumer attitudes.We designed two pairs of coffee packages for the study. Each pair comprised a neo-retro style version of the package and a plain-style version of the package. A different brand establishment date was included on each pair of coffee packages. We then conducted an online experiment in which participants were shown 1 of the 4 package versions, assigned in a random manner. They were asked to rate the package against different criteria on a series of Osgood or Likert scales. A step-by-step tutorial demonstrates how to analyse the dataset using factorial ANOVA with SPSS software. Factorial ANOVA allows us to explore the combined impact of packaging style and date of brand establishment on consumer attitudes. We explain how to interpret these charts and statistical results. The dataset is accompanied by a Student Guide and How-to Guide for SPSS.
Encyclopedia of Research Design
"Comprising more than 500 entries, the Encyclopedia of Research Design explains how to make decisions about research design, undertake research projects in an ethical manner, interpret and draw valid inferences from data, and evaluate experiment design strategies and results. Two additional features carry this encyclopedia far above other works in the field: bibliographic entries devoted to significant articles in the history of research design and reviews of contemporary tools, such as software and statistical procedures, used to analyze results. It covers the spectrum of research design strategies, from material presented in introductory classes to topics necessary in graduate research; it addresses cross- and multidisciplinary research needs, with many examples drawn from the social and behavioral sciences, neurosciences, and biomedical and life sciences; it provides summaries of advantages and disadvantages of often-used strategies; and it uses hundreds of sample tables, figures, and equations based on real-life cases."--Publisher's description.
An Introduction to the Analysis of Variance
This book is for students taking either a first-year graduate statistics course or an advanced undergraduate statistics course in Psychology. Enough introductory statistics is briefly reviewed to bring everyone up to speed. The book is highly user-friendly without sacrificing rigor, not only in anticipating students' questions, but also in paying attention to the introduction of new methods and notation. In addition, many topics given only casual or superficial treatment are elaborated here, such as: the nature of interaction and its interpretation, in terms of theory and response scale transformations; generalized forms of analysis of covariance; extensive coverage of multiple comparison methods; coverage of nonorthogonal designs; and discussion of functional measurement. The text is structured for reading in multiple passes of increasing depth; for the student who desires deeper understanding, there are optional sections; for the student who is or becomes proficient in matrix algebra, there are still deeper optional sections. The book is also equipped with an excellent set of class-tested exercises and answers.