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Political analysis : a guide to data & statistics / Matthew Loveless.

By: Loveless, Matthew [author.].Publisher: Los Angeles ; London : SAGE, 2023Description: vi, 492 pages : illustrations (black and white).Content type: text | still image Media type: unmediated Carrier type: volumeISBN: 9781529774849; 9781529774832.Subject(s): Political statisticsDDC classification: 320.0727
Contents:
The scientific method and statistics -- Theory and hypotheses -- Data and variables -- Research and design -- Statistics and the scientific study of politics -- I. 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 -- II. Inferential statistics -- An introduction to inference -- Inference for nominal- and ordinal-level variables -- The central limit theorem -- Inference for interval-level variables -- III. Multiple regression -- Multiple regression -- Extensions to multiple regression -- Issues with multiple regression -- Binary logistics regression -- Categorical and limited dependent variables -- IV. Current debates -- Big alternatives -- The ethics of data analysis.
Holdings
Item type Current library Class number Status Barcode
Book House of Lords Library - Palace Dewey 320.0727 LOV (Browse shelf(Opens below)) Available 021803

The scientific method and statistics -- Theory and hypotheses -- Data and variables -- Research and design -- Statistics and the scientific study of politics -- I. 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 -- II. Inferential statistics -- An introduction to inference -- Inference for nominal- and ordinal-level variables -- The central limit theorem -- Inference for interval-level variables -- III. Multiple regression -- Multiple regression -- Extensions to multiple regression -- Issues with multiple regression -- Binary logistics regression -- Categorical and limited dependent variables -- IV. Current debates -- Big alternatives -- The ethics of data analysis.

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