Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, this textbook provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.
Covering basic univariate and bivariate statistics and regression models for nominal, ordinal, and interval outcomes, this textbook provides graduate students in the social and health sciences with fundamental skills to estimate, interpret, and publish quantitative research using contemporary standards.
Rachel A. Gordon is Associate Dean for Research and Administration and Professor of Health Studies in the College of Health and Human Sciences at Northern Illinois University, USA. Professor Gordon has multidisciplinary substantive and statistical training and a keen interest in teaching and disseminating applied statistics within the health and social sciences.
Inhaltsangabe
Part I: Getting ready 1 Considering Examples of Scholarly Publications Modeling Social and Health Variables 2 Planning and Starting a Quantitative Research Project with Existing Data Part II: Describing the data 3 Graphing and Summarizing Individual Variables 4 Introducing Population Estimation and Hypothesis Testing 5 Estimating and Testing the Association between Two Variables Part III: Estimating and presenting linear regression models 6 Introducing the Linear Regression Model with Two Continuous Variables 7 Considering Nonlinearity and Nonconstant Variance 8 Including Categorical Predictor Variables 9 Including More Than One Predictor Variable in the Model 10 Considering Interactions among Predictor Variables Part IV: Estimating and presenting generalized linear models 11 Introducing the Generalized Linear Regression Model 12 Analyzing Dichotomous Outcomes 13 Analyzing Multi-Category Outcomes and Offering a Roadmap to Additional Models
Part I: Getting ready 1 Considering Examples of Scholarly Publications Modeling Social and Health Variables 2 Planning and Starting a Quantitative Research Project with Existing Data Part II: Describing the data 3 Graphing and Summarizing Individual Variables 4 Introducing Population Estimation and Hypothesis Testing 5 Estimating and Testing the Association between Two Variables Part III: Estimating and presenting linear regression models 6 Introducing the Linear Regression Model with Two Continuous Variables 7 Considering Nonlinearity and Nonconstant Variance 8 Including Categorical Predictor Variables 9 Including More Than One Predictor Variable in the Model 10 Considering Interactions among Predictor Variables Part IV: Estimating and presenting generalized linear models 11 Introducing the Generalized Linear Regression Model 12 Analyzing Dichotomous Outcomes 13 Analyzing Multi-Category Outcomes and Offering a Roadmap to Additional Models
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