The Essentials of Political AnalysisProviding a strong conceptual foundation, The Essentials of Political Analysis walks students through the basics of measuring concepts, formulating and testing hypotheses, and describing variables. The author's engaging and straightforward prose clearly introduces key terms and concepts while chapter-opening objectives cue students to learning goals. Over eighty tables and figures enhance important textual material. Class-tested chapter exercises promote skill application and aid student review. Fans of Pollock's practical introduction to the methods course will appreciate the second edition's many improvements, from more comparative and international material to a brand new chapter on logistic regression. Introducing students to one of the discipline's most widely used statistical tools, students learn the logic of logistic regression, maximum likelihood estimation and how to convert logic into probabilities. |
From inside the book
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Page 180
... logistic regression is similar to OLS regression . Like OLS , logistic regression gauges the effect of the independent variable by estimating an intercept and a slope , both familiar fixtures of linear regression . Plus logistic regression ...
... logistic regression is similar to OLS regression . Like OLS , logistic regression gauges the effect of the independent variable by estimating an intercept and a slope , both familiar fixtures of linear regression . Plus logistic regression ...
Page 187
... would have Logged odds ( voting ) = -1.581 +.180 ( education ) . The coefficients tell us that , for individuals with no Logistic Regression 187 8-3 Education and Voting: Logistic Regression Coefficients and Related Statistics.
... would have Logged odds ( voting ) = -1.581 +.180 ( education ) . The coefficients tell us that , for individuals with no Logistic Regression 187 8-3 Education and Voting: Logistic Regression Coefficients and Related Statistics.
Page 195
... regression model , we find Logged odds ( voting ) = −2.022 + .194 ( education ) + 1.539 ( partisan ) . Table 8-8 Education , Partisan Strength , and Voting : Logistic Regression 195 Logistic Regression with Multiple Independent Variables.
... regression model , we find Logged odds ( voting ) = −2.022 + .194 ( education ) + 1.539 ( partisan ) . Table 8-8 Education , Partisan Strength , and Voting : Logistic Regression 195 Logistic Regression with Multiple Independent Variables.
Contents
What This Book Is and Is Not About | 2 |
The Measurement of Concepts | 9 |
Explanations and Hypotheses | 29 |
Copyright | |
14 other sections not shown
Common terms and phrases
abortion analysis applied association attendance average calculated chance Chapter chi-square coded column comparing comparison concept consider countries Democrats dependent describe difference discussed distribution divided effect Election equal estimate example explanation fall favor female Figure freedom gender high school higher increase independent variable individuals inference interested interpret less likelihood logged odds logistic regression lower males measure normal Note null hypothesis observed obtain odds of voting opinions partisan party percent percentage political population positive predicted probability probability of voting problem produce proportion provides question R-square random sampling error relationship reported Republican researcher respondents sample mean score shows significance Social South square standard deviation standard error statistic strength strong Study subjects Suppose Survey Table tells tion true turnout units variation voters women