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POLS 210 Assignment 1 and Measurement

by: Justice Notetaker

POLS 210 Assignment 1 and Measurement POLS 210

Marketplace > Ball State University > Political Science > POLS 210 > POLS 210 Assignment 1 and Measurement
Justice Notetaker
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About this Document

Some of these things will definitely be on our Exam
Political Science Research Methods
Class Notes




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This 2 page Class Notes was uploaded by Justice Notetaker on Wednesday January 20, 2016. The Class Notes belongs to POLS 210 at Ball State University taught by Nishikawa in Winter 2016. Since its upload, it has received 40 views. For similar materials see Political Science Research Methods in Political Science at Ball State University.


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Date Created: 01/20/16
 Introduction to Assignment 1  Major Goals:  Learn political science research methods  Science  Objective  Theory, hypothesis, observations  Using data  Quantitative analysis  Compare  Generalization  Cause & effects  Bivariate & multivariate analysis  Research Process  Research question  Literature review  Theory & hypothesis  Methods/ Operationalization  Testing hypothesis  Stats  Conclusion  How to pick your research question  Examples:  Why are some countries are more likely to be involved in international conflicts than others?  Why do some countries have a higher level of democratic performance than others?  Units of analysis  Countries  States  Individuals  NO normative questions  Cant use the word “should” (too opinionated)  NO factual questions  “What’s the population of China?”  Only ONE outcome factor (dependent variable)  No changes over time  Measurement  Concepts of measurement  Labels of observable phenomena  Ideas  EX: world peace, political trust, gender gap, etc.  Problems in Operationalization  Operationalization: theory to data  Concepts are multidimensional  Liberalism  EX: social (gay rights, abortion)  Econ. (size of gov’t, welfare)  Concepts and variables  Theory  data  Broad  specific  EX: political participation  Reliability and validity (ON TEST)  Reliability: consistency, same results  Validity: intention, are you measuring what you wanted  Inflation: when the sample population is larger than the true population  Measurement Error  Systematic Error  validity issues  Random Error  reliability issues  Statistically can’t get rid of systematic errors be cause they are more difficult to deal with  Units of analysis (again)  Countries  States  Individuals  Difference between individual & aggregate level data  Individual test scores  average test score  Individual income  average income  Individual background  % minority  Ecological Fallacy: using aggregate level data to answer individual level research questions  Research question and data should be at the same level  Levels of measurement  Nominal: with categories, without direction (no order)  EX: gender, race, ethnicity, religion  Ordinal: with categories, with direction (can be ranked)  EX: age, agree strongly, agree somewhat, disagree  Interval/ratio: with direction, without categories (numbers)  EX: dollar amount, percentages, ages (25, 10, 15, etc.)  Most sophisticated


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