- ホーム
- > 洋書
- > 英文書
- > Politics / International Relations
Full Description
Statistics are part of our everyday life: from polling and elections to advertising claims, we confront numerical claims all the time. Rather than being swayed by bad arguments and questionable correlations, this book introduces you to the most common and contemporary statistical methods so that you can better understand the world.
This is the most accessible guide to using statistics in Politics and IR research. Praised for being intuitive and engaging, this textbook walks you through the most common tools - from crosstabs to correlations; from multiple to logistic regression - in a way that couldn't be more different than dull number crunching or complicated techniques. Instead, it empowers you to decide the best means to analyse a problem.
Fully updated and revised throughout, this new edition is accompanied by four workbooks that provide both practical and theoretical examples using different statistical software: SPSS, Stata, R, and Python. Simply choose the relevant workbook and learn how to do your own statistical analysis with the included activities, screenshots and step-by-step instructions.
This text is essential for anyone looking to become proficient in statistics: whether that's to gain statistical literacy, to complete your thesis, to boost your value on the job market, or to become an active and informed consumer of current affairs.
Why let other people explain the world to you?
Matthew Loveless is an Associate Professor in the Department of Political and Social Sciences at the University of Bologna, Italy.
Contents
Chapter 1: The Scientific Method and Statistics
Chapter 2: Theory and Hypotheses
Chapter 3: Data and Variables
Chapter 4: Research Design and the Scientific Study of Politics
Chapter 5: The Ethics of Data Analysis
PART I Descriptive Statistics
Chapter 6: Univariate Descriptive Statistics
Chapter 7: Measures of Association I: Nominal- and Ordinal-level Variables
Chapter 8: Measures of Association II: Means Comparison and Correlation
Chapter 9: Measures of Association III: (Bivariate) Regression
PART II Inferential Statistics
Chapter 10: An Introduction to Interference
Chapter 11: Inference for Nominal- and Ordinal-level Variables
Chapter 12: The Central Limit Theorem
Chapter 13: Inference for Interval-level Variables
PART III Multiple Regression
Chapter 14: Multiple Regression
Chapter 15: Extensions to Multiple Regression
Chapter 16: Issues with Multiple Regression
Chapter 17: Binary Logistic Regression
Chapter 18: Categorical and Limited Dependent Variables Epilogue
