Apply statistics to your everyday life. Statistics and Data Analysis for Social Science helps students to build a strong foundational understanding of statistics by providing clarity around when and why statistics useful. Rather than focusing on the “how to” of statistics, author Eric J. Krieg simplifies the complexity of statistical calculations by introducing only what is necessary to understanding each concept. Every chapter is written around and applied to a different social problem or issues–enabling students to broaden their imagination about the statistical “tools” that can be used to make sense of our world and, maybe, to make the world a better place. In addition to updating all the tables and examples with new data, the Second Edition has replaced the section on SPSS with three new sets of exercises at the end of each chapter:  1. Chapter Exercises for students complete during their reading and bring questions to class,  2. In-Class Exercises that focus on the areas that students struggled with during their reading, and  3.  Homework Exercises that can be assigned if students need extra practice with the concepts.

Correlation and Regression

Correlation and Regression

Correlation and Regression

Two uniformed boys are seen sitting outside on a woven mat mounted on a wooden frame. They are reading a book together.



On average, how many years of education does it take to reach an income level of $75,000? On average, how much is a student’s grade point average (GPA) lowered for each hour of television watched per day? Do countries with higher median household incomes tend to have higher literacy rates? These and other questions like them can be answered using statistics known as correlation and regression. In previous chapters, we learned how to describe the relationship between two nominal variables (phi, C, V, and lambda), between a nominal variable and an ordinal variable (phi, C, V, and lambda), between two ordinal variables (gamma and Somer’s d), and between a nominal variable and an interval/ratio variable (eta2). Correlation ...

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