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Unlocking Statistics for the Social Sciences provides comprehensive guidance for students and novice researchers. Although the focus is on data analysis techniques, students will discover or rediscover the connections between research design, associated data analysis, interpretation and reporting of data analysis results. The first two chapters review quantitative research methods and introduce students to the important process of collecting, cleaning and screening data for analysis. Each subsequent chapter covers the characteristics of an intermediate statistical technique, associated assumptions, related research designs, step-by-step instructions for data analysis, and a sample report of analysis results. Statistical procedures include parametric tests like analysis of variance and linear regression as well as their nonparametric counterparts. Data from around the world expose students to authentic, real-world research contexts. Key features:
Outlines of research plans that drive statistical procedures Chapter opening vignettes and case studies Step-by-step data analysis instructions using SPSS screenshots Computation of measures of effect size, confidence intervals and power analysis Guidelines for interpreting data analysis results
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Unlocking Statistics for the Social Sciences provides comprehensive guidance for students and novice researchers. Although the focus is on data analysis techniques, students will discover or rediscover the connections between research design, associated data analysis, interpretation and reporting of data analysis results. The first two chapters review quantitative research methods and introduce students to the important process of collecting, cleaning and screening data for analysis. Each subsequent chapter covers the characteristics of an intermediate statistical technique, associated assumptions, related research designs, step-by-step instructions for data analysis, and a sample report of analysis results. Statistical procedures include parametric tests like analysis of variance and linear regression as well as their nonparametric counterparts. Data from around the world expose students to authentic, real-world research contexts. Key features:
Outlines of research plans that drive statistical procedures Chapter opening vignettes and case studies Step-by-step data analysis instructions using SPSS screenshots Computation of measures of effect size, confidence intervals and power analysis Guidelines for interpreting data analysis results