Applied Statistics for the Social and Health Sciences
eBook - ePub

Applied Statistics for the Social and Health Sciences

  1. 780 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Applied Statistics for the Social and Health Sciences

About this book

Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, Applied Statistics for the Social and Health Sciences provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.

Reflecting the growing importance of "Big Data" in the social and health sciences, this thoroughly revised and streamlined new edition covers best practice in the use of statistics in social and health sciences, draws upon new literatures and empirical examples, and highlights the importance of statistical programming, including coding, reproducibility, transparency, and open science.

Key features of the book include:

  • interweaving the teaching of statistical concepts with examples from publicly available social and health science data and literature excerpts;
  • thoroughly integrating the teaching of statistical theory with the teaching of data access, processing, and analysis in Stata;
  • recognizing debates and critiques of the origins and uses of quantitative methods.

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Yes, you can access Applied Statistics for the Social and Health Sciences by Rachel A. Gordon in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Endorsement Page
  3. Half-Title Page
  4. Title Page
  5. Copyright Page
  6. Dedication Page
  7. Table of Contents in Brief
  8. Table of Contents in Detail
  9. Preface
  10. Part I Getting Ready
  11. Part II Describing the Data
  12. Part III Estimating and Presenting Linear Regression Models
  13. Part IV Estimating and Presenting Generalized Linear Models
  14. Glossary/Index