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This full year module shares the Autumn term lectures and classes with Researching Social Life II (SC203). In this part of the module, students are introduced to quantitative data analysis. The second term builds on the knowledge gained in the first and introduces students to the study of stratification across the life course, with an emphasis on the critical examination of empirical evidence on inequality in both Britain and the USA.
In the autumn this module introduces you to the principles and practice of quantitative data analysis. Over ten weeks, students are first introduced to basic descriptive statistics and the fundamental concepts of statistical inference, then to measures of association for both continuous and categorical variables. The term ends with a focus on regression analysis, which is the most commonly used statistical model in social science. Students will learn how to conduct statistical analysis using IBM SPSS software in weekly lab sessions.
In the spring term, building on the knowledge gained in the previous term, students are exposed to a selective introduction to the study of stratification across the life course, with an emphasis on the examination of empirical evidence from Britain and the USA. Social stratification is the unequal distribution of scarce resources, and of the processes by which these resources are allocated to individuals, groups, and social positions. The study of stratification is broad and occupies a central role in sociological research, encompassing studies of income and wealth inequality, occupational and class hierarchies, inequality of educational opportunity, poverty, social mobility between and within generations, gender and race-ethnic inequality, and the consequences of inequality. We will also pay particular attention to the life course perspective on stratification; in other words, how experiences in early life influence later events and choices in education, marriage, or health. In this ten week course, we examine specific examples of sociological research in selected areas, covering the concepts, theories, facts, and methods of analysis used by sociologists to understand different aspects of social stratification. The examples are not meant to provide a comprehensive overview, but rather to illustrate prominent questions in the field and how sociologists go about answering them.
After the introductory week, this course is divided into four two-week sections, each devoted to a stage in the life course. Every section contains two lectures (one each week), followed by a class discussion after the first lecture and a lab session after the second. The class discussion will include in-depth discussion of the readings, with particular attention paid to identifying the research question and discussing the analytical choices and evidence provided by the authors. The class takes most of its examples from the contemporary United Kingdom and the United States. In each lab session, we will formulate our own research questions and hypotheses based on our readings and discussions. Building on knowledge and skills gained in the autumn term, students will then use SPSS software to test these using data from the largest longitudinal study of UK households: Understanding Society (UKHLS).
In the process of taking this module, you will develop skills that are transferable to your undergraduate project, the labour market, or postgraduate work, when you complete your undergraduate studies. You will also appreciate more how sociologists go about applying their skills and knowledge to the empirical investigation of issues they study. Chiefly, upon successful completion of the module, you will:
1. Have gained an understanding of the principles and practice of quantitative analysis in sociology
2. Have gained an understanding of the fundamentals of statistical inference
3. Have basic skills in analysing and presenting quantitative data using computer software IBM SPSS and Excel
4. Gain a substantive understanding of current key debates and recent empirical work in the field of social stratification
5. Have an improved ability to critically read scientific journal articles and to interpret quantitative evidence
6. Gain the ability to critically examine the link between theoretical framework, research questions, data choice, and modelling strategy
7. Be able to formulating research questions and testable hypotheses, and applying these to real data
- Module Supervisor: Nick Allum
- Module Supervisor: Isabel Crowhurst
- Module Supervisor: Neli Demireva
- Module Supervisor: Renee Luthra
- Module Supervisor: Katy Wheeler