• Getting started. How to read this book
• Introduction to How to write a BA thesis, second edition
• Useful nuts and bolts
• More nuts and bolts
• Framing your topic. Taking effective notes and avoiding plagiarism
• How to build a reading list
• Refining your topic, writing a proposal, and beginning research
• Conducting your research. What is good thesis research
• Using case studies effectively
• Every thesis should have a thesis
• Writing your best. Planning and prewriting: how do they help your thesis?
• Writing your best
• Effective openings, smooth transitions, and strong closings
• Good editing makes good writing
• Presenting information visually
• Presenting your work to others
• Working your best. Working efficiently
• Overcoming problems
• What to do if you get stuck
• Scheduling and completing your thesis. Thesis schedule
• Tips and reminders
• Frequently asked questions
• What to do when you're all done
• Dealing with special requirements. Thesis defense and second readers: questions and answers
• A one-semester thesis
• Citing your sources and getting more advice. Appendix 1: Best sources for more help
• Appendix 2: Footnotes 101
• Appendix 3: Advice for new faculty advisers.

How to Write a BA Thesis is the only book that directly addresses the needs of undergraduate students writing a major paper. This book offers step-by-step advice on how to move from early ideas to finished paper. It covers choosing a topic, selecting an advisor, writing a proposal, conducting research, developing an argument, writing and editing the thesis, and making through a defense. Lipson also acknowledges the challenges that arise when tackling such a project, and he offers advice for breaking through writer's block and juggling school-life demands. This is a must-read for anyone writing a BA thesis, or for anyone who advises these students.
(source: Nielsen Book Data)

• Chapter 1: Introduction Research on Inequality Who Votes
• Who Doesn't? Politics and the Gender Gap Repression of Human Rights A Look into Judicial Decision Making and Its Effects Influencing Bureaucracies Effects of Campaign Advertising on Voters Research on Public Support for US Foreign Involvement Conclusion Terms Introduced Notes Chapter 2: The Empirical Approach to Political Science Elements of Empiricism The Importance of Theory A Brief Overview of the Empirical Research Process Reactions to the Empirical Approach: Practical Objections Competing Points of View Conclusion Terms Introduced Suggested Readings Notes Chapter 3: Beginning the Research Process: Identifying a Research Topic, Developing Research Questions, and Reviewing the Literature Specifying the Research Question Sources of Ideas for Research Topics Why Conduct a Literature Review? Collecting Sources for a Literature Review Writing a Literature Review Anatomy of a Literature Review Conclusion Terms Introduced Suggested Readings Notes Chapter 4: The Building Blocks of Social Scientific Research: Hypotheses, Concepts, and Variables Proposing Explanations Formulating Hypotheses Defining Concepts Conclusion Terms Introduced Suggested Readings Notes Chapter 5: The Building Blocks of Social Scientific Research: Measurement Devising Measurement Strategies Examples of Political Measurements: Getting to Operationalization The Accuracy of Measurements The Precision of Measurements Multi-Item Measures Conclusion Terms Introduced Suggested Readings Notes Chapter 6: Research Design: Making Causal Inferences Verifying Causal Assertions Other Randomized Experiments Nonrandomized Designs: Quasi-Experiments Natural Experiments Observational Studies Longitudinal (Time Series) Designs Conclusion Terms Introduced Suggested Readings Notes Chapter 7: Sampling The Basics of Sampling Types of Samples What Can Be Learned from a Sample of a Population Conclusion Terms Introduced Suggested Readings Notes Chapter 8: Making Empirical Observations: Firsthand Observation Types of Data and Collection Techniques Firsthand, Direct Observation Firsthand, Indirect Observation Ethical Issues in Observation Conclusion Terms Introduced Suggested Readings Notes Chapter 9: Document Analysis: Using the Written Record Content Analysis Types of Written Records Advantages and Disadvantages of the Written Record Conclusion Terms Introduced Suggested Readings Notes Chapter 10: Survey Research and Interviewing Fundamentals: Ensuring Validity and Reliability Survey Research Using Archived Surveys Interviewing Conclusion Terms Introduced Suggested Readings Notes Chapter 11: Making Sense of Data: First Steps The Data Matrix Descriptive Statistics Graphs for Presentation and Exploration What's Next Terms Introduced Suggested Readings Notes Chapter 12: Statistical Inference Two Kinds of Inference Confidence Intervals and Confidence Levels Conclusion Terms Introduced Suggested Readings Notes Chapter 13: Investigating Relationships between Two Variables The Basics of Identifying and Measuring Relationships Table Summaries of Categorical Variable Associations Measuring Strength of Relationships in Tables The Relationship between a Categorical and a Quantitative Variable Regression Analysis Conclusion Appendix: Regression Assumptions Terms Introduced Suggested Readings Notes Chapter 14: Multivariate Analysis Holding a Variable Constant Multivariate Analysis of Categorical Data Linear Models Categorical Variables and Linear Models Logistic Regression Conclusion Terms Introduced Suggested Readings Notes Chapter 15: The Research Report: An Annotated Example Annotated Research Report Example.
• (source: Nielsen Book Data)

Step by step, Political Science Research Methods walks students through the logic of research design, carefully explaining how researchers choose which method to employ. The Eighth Edition of this trusted resource offers a greater emphasis on the ways in which particular methods are used by undergraduates, expanded coverage of the role of the Internet in research and analysis, and more international examples. In the new fourth edition of the accompanying workbook, Working with Political Science Research Methods, students are given the perfect opportunity to practice each of the methods presented in the core text. This helpful supplement breaks each aspect of the research process into manageable parts and features new exercises and updated data sets. A solutions manual with answers to the workbook is available to adopters. ? New to this edition: *Streamlined content that delivers greater clarity of concepts and a tighter focus on what matters most: *simplified, clear discussion of statistical inference and hypothesis testing; *updated examination of multivariate data analysis, with a sharper focus on the most important techniques; and *more examples of calculations *Learning objectives encourage close, focused reading and measurable takeaways *New and updated examples of research serve as touchstones throughout the book and demonstrate a greater variety of data collection methods: *the gender gap in politics; *income inequality and political representation; *the impact of SuperPAC advertising; *repression of human rights; *the public's sensitivity to the unequal distribution of war casualties across American communities; and *increasingly politicized views of the Supreme Court *Greater emphasis on how particular research methods are used by undergraduate students *Expanded coverage of the role of the Internet in research and analysis *A brand new annotated research article in Chapter 15.
(source: Nielsen Book Data)

Dewey, Bellow, Strauss, Friedman - the University of Chicago has been the home of some of the most important thinkers of the modern age. But perhaps no name has been spoken with more respect than Turabian. The dissertation secretary at Chicago for decades, Kate L. Turabian literally wrote the book on the successful completion and submission of the student paper. Her "Manual for Writers of Research Papers, Theses, and Dissertations", created from her years of experience with research projects across all fields, has sold more than seven million copies since it was first published in 1937. Now, with this seventh edition, "Turabian's Manual" has undergone its most extensive revision, ensuring that it will remain the most valuable handbook for writers at every level - from first-year undergraduates, to dissertation writers apprehensively submitting final manuscripts, to senior scholars who may be old hands at research and writing but less familiar with new media citation styles. Gregory G. Colomb, Joseph M. Williams, and the late Wayne C. Booth - the gifted team behind "The Craft of Research" - and the University of Chicago Press Editorial Staff combined their wide-ranging expertise to remake this classic resource. They preserve Turabian's clear and practical advice while fully embracing the new modes of research, writing, and source citation brought about by the age of the Internet.
(source: Nielsen Book Data)

• Preface ix 1 The Science in Social Science 3 1.1 Introduction 3 1.1.1 Two Styles of Research, One Logic of Inference 3 1.1.2 Defining Scientific Research in Social Sciences 7 1.1.3 Science and Complexity 9 1.2 Major Components of Research Design 12 1.2.1 Improving Research Questions 14 1.2.2 Improving Theory 19 1.2.3 Improving Data Quality 23 1.2.4 Improving the Use of Existing Data 27 1.3 Themes of This Volume 28 1.3.1 Using Observable Implications to Connect Theory and Data 28 1.3.2 Maximizing Leverage 29 1.3.3 Reporting Uncertainty 31 1.3.4 Thinking like a Social Scientist: Skepticism and Rival Hypotheses 32 2 Descriptive Inference 34 2.1 General Knowledge and Particular Facts 35 2.1.1 "Interpretation" and Inference 36 2.1.2 "Uniqueness, " Complexity, and Simplification 42 2.1.3 Comparative Case Studies 43 2.2 Inference: the Scientific Purpose of Data Collection 46 2.3 Formal Models of Qualitative Research 49 2.4 A Formal Model of Data Collection 51 2.5 Summarizing Historical Detail 53 2.6 Descriptive Inference 55 2.7 Criteria for Judging Descriptive Inferences 63 2.7.1 Unbiased Inferences 63 2.7.2 Efficiency 66 3 Causality and Causal Inference 75 3.1 Defining Causality 76 3.1.1 The Definition and a Quantitative Example 76 3.1.2 A Qualitative Example 82 3.2 Clarifying Alternative Definitions of Causality 85 3.2.1 "Causal Mechanisms" 85 3.2.2 "Multiple Causality" 87 3.2.3 "Symmetric" and "Asymmetric" Causality 89 3.3 Assumptions Required for Estimating Causal Effects 91 3.3.1 Unit Homogeneity 91 3.3.2 Conditional Independence 94 3.4 Criteria for Judging Causal Inferences 97 3.5 Rules for Constructing Causal Theories 99 3.5.1 Rule
• 1: Construct Falsifiable Theories 100 3.5.2 Rule
• 2: Build Theories That Are Internally Consistent 105 3.5.3 Rule
• 3: Select Dependent Variables Carefully 107 3.5.4 Rule
• 4: Maximize Concreteness 109 3.5.5 Rule
• 5: State Theories in as Encompassing Ways as Feasible 113 4 Determining What to Observe 115 4.1 Indeterminate Research Designs 118 4.1.1 More Inferences than Observations 119 4.1.2 Multicollinearity 122 4.2 The Limits of Random Selection 124 4.3 Selection Bias 128 4.3.1 Selection on the Dependent Variable 129 4.3.2 Selection on an Explanatory Variable 137 4.3.3 Other Types of Selection Bias 138 4.4 Intentional Selection of Observations 139 4.4.1 Selecting Observations on the Explanatory Variable 140 4.4.2 Selecting a Range of Values of the Dependent Variable 141 4.4.3 Selecting Observations on Both Explanatory and Dependent Variables 142 4.4.4 Selecting Observations So the Key Causal Variable Is Constant 146 4.4.5 Selecting Observations So the Dependent Variable Is Constant 147 4.5 Concluding Remarks 149 5 Understanding What to Avoid 150 5.1 Measurement Error 151 5.1.1 Systematic Measurement Error 155 5.1.2 Nonsystematic Measurement Error 157 5.2 Excluding Relevant Variables: Bias 168 5.2.1 Gauging the Bias from Omitted Variables 168 5.2.2 Examples of Omitted Variable Bias 176 5.3 Including Irrelevant Variables: Inefficiency 182 5.4 Endogeneity 185 5.4.1 Correcting Biased Inferences 187 5.4.2 Parsing the Dependent Variable 188 5.4.3 Transforming Endogeneity into an Omitted Variable Problem 189 5.4.4 Selecting Observations to Avoid Endogeneity 191 5.4.5 Parsing the Explanatory Variable 193 5.5 Assigning Values of the Explanatory Variable 196 5.6 Controlling the Research Situation 199 5.7 Concluding Remarks 206 6 Increasing the Number of Observations 208 6.1 Single-Observation Designs for Causal Inference 209 6.1.1 "Crucial" Case Studies 209 6.1.2 Reasoning by Analogy 212 6.2 How Many Observations Are Enough? 213 6.3 Making Many Observations from Few 217 6.3.1 Same Measures, New Units 219 6.3.2 Same Units, New Measures 223 6.3.3 New Measures, New Units 224 6.4 Concluding Remarks 229 References 231 Index 239.
• (source: Nielsen Book Data)

While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research performed in this field. These leading scholars, each representing diverse academic traditions, have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. Their book demonstrates that the same logic of inference underlies both good quantitative and good qualitative research designs, and their approach applies equally to each. Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and uncertainty of empirical inferences, discovering causal effects, and generally improving qualitative research. Among the specific topics they address are interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed. The unified logic of inference that this book explicates will be enormously useful to qualitative researchers of all traditions and substantive fields.
(source: Nielsen Book Data)