Test Bank Starting Out in Methods and Statistics for Psychology a Hands-on Guide to Doing Research by Victoria Bourne

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Test Bank Starting Out in Methods and Statistics for Psychology a Hands-on Guide to Doing Research by Victoria Bourne

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Test Bank Starting Out in Methods and Statistics for Psychology a Hands-on Guide to Doing Research by Victoria Bourne

Starting Out in Methods and Statistics for Psychology: a Hands-on Guide to Doing Research takes first year psychology students through the entire process of doing research in psychology, from exploring designs and methods, to conducting step-by-step, by-hand data analysis, and writing up their findings, all in a friendly and accessible way.

ISBN-10 โ€ : โ€Ž 0198753330
ISBN-13 โ€ : โ€Ž 978-0198753339

Victoria Bourne (Author)

Table Of Contents
Part One: Introduction
1:An overview of how to do research
2:How to design a psychological study: the basics of methodology
3:How to find, read, write and think about research papers
4:Qualitative methods in psychological research
5:The basics of statistical analysis
Part Two: Experimental Design
6:How to design an experiment
7:How can I tell if scores differ between two groups? Independent t test
8:How can I tell if scores differ between two conditions? Repeated t test
9:How can I tell if scores differ between three or more groups? One-way independent measures ANOVA
Part Three: Correlational Design
10:How to design a correlational study
11:How can I tell if two variables are correlated? Pearsons correlation
12:How can I tell if one variable can predict another? Simple linear regression
Part Four: Non-parametric Statistics
13:When and why might I need to use non-parametric statistics?
14:Do my data fit the expected frequencies? Chi square
15:Are there differences between groups or conditions? Mann-Whitney U and Wilcoxon signed rank tests
16:Is there a relationship between two variables? Spearmanโ€™s correlation
Part Five: Beyond the Basics
17:Which statistical test should I use?
18:Moving beyond the basics of research and analysis: how do I understand more complicated research designs?