Description
Why let other people explain the world to you?
From news reporting on elections or unfolding political crises to everyday advertising, you are confronted with statistics. 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. It′s not about mindless number crunching or flashy techniques but about knowing when to use statistics as the best means to analyse a problem.
Whether you want to answer:
"Who is most likely to turn out and vote at the next election?"
or
"What accounts for some political conflicts escalating to war?"
you’ll explore what can and can’t be done with statistics, and how to select the most appropriate statistical techniques and correctly interpret the results.
Perhaps you simply want to understand enough to pass your statistics class and move on. Maybe you want to build your knowledge so that you are not excluded from research and debate. Or it could be the first step towards more advanced study. Whatever your goal, this book guides you through the journey, empowering you to confidently interact with statistics to make you a more formidable student, employee, and democratic citizen.
Table of Contents
The Scientific Method And Statistics
Theory And Hypotheses
Data And Variables
Research Design
Statistics And The Scientific Study Of Politics
Descriptive Statistics
Univariate Descriptive Statistics
Measures Of Association I: Nominal- And Ordinal-Level Variables
Measures Of Association II: Means Comparison And Correlation
Measures Of Association III: (Bivariate) Regression
Inferential Statistics
An Introduction To Inference
Inference For Nominal- & Ordinal-level Variables
The Central Limit Theorem
Inference For Interval-Level Variables
Multiple Regression
Multiple Regression
Extensions To Multiple Regression
Issues With Multiple Regression
Binary Logistic Regression
Categorical And Limited Dependent Variables
Current Debates
Big Alternatives
The Ethics Of Data Analysis
