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  • Produktbild: Presenting Statistical Results Effectively
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Presenting Statistical Results Effectively

47,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.12.2021

Verlag

Sage Publications

Seitenzahl

456

Maße (L/B/H)

24,6/18,9/2,4 cm

Gewicht

875 g

Sprache

Englisch

ISBN

978-1-4462-6981-7

Beschreibung

Rezension

Is your quantitative work so screamingly clear that your readers never misunderstand your figures, misread your tables, or get confused by your prose?  If so, then don't waste your time with Andersen and Armstrong's thoughtful book about the effective presentation and interpretation of statistical results. Gary King 20210627

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

25.12.2021

Verlag

Sage Publications

Seitenzahl

456

Maße (L/B/H)

24,6/18,9/2,4 cm

Gewicht

875 g

Sprache

Englisch

ISBN

978-1-4462-6981-7

EU-Ansprechpartner

Zeitfracht Medien GmbH
Ferdinand-Jühlke-Straße 7|99095|Erfurt|DE

Herstelleradresse

SAGE Publications
1 Oliver's Yard 55 City Road|EC1Y 1SP|London|GB

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Die Leseprobe wird geladen.
  • Produktbild: Presenting Statistical Results Effectively
  • Produktbild: Presenting Statistical Results Effectively
  • Chapter 1: Some Foundation
    What is a 'Model'?
    Statistical Inference
    Part A: General Principles of Effective Presentation
    Chapter 2: Best Practices for Graphs and Tables
    When to use Tables and Graphs
    Constructing Effective Tables
    Constructing Clear and Informative Graphs
    Chapter 3: Methods for Visualizing Distributions
    Displaying the Distributions of Categorical Variables
    Displaying Distributions of Quantitative Variables
    Transformations
    Chapter 4: Exploring and Describing Relationships
    Two Categorical Variables
    Categorical Explanatory Variable and Quantitative Dependent Variable
    Two quantitative Variables
    Multivariate Displays
    Part B: The Linear Model
    Chapter 5: The Linear Regression Model
    Ordinary Least Squares Regression
    Hypothesis tests and confidence intervals
    Assessing and Comparing Model Fit
    Relative Importance of Predictors
    Interpreting and presenting OLS models: Some empirical examples
    Linear Probability Model
    Chapter 6: Assessing the Impact and Importance of Multi-category Explanatory Variables
    Coding Multi-category Explanatory Variables
    Revisiting Statistical Significance: Multi-category Predictors
    Relative importance of sets of regressors
    Graphical Presentation of Additive Effects
    Chapter 7: Identifying and Handling Problems in Linear Models
    Nonlinearity
    Influential Observations
    Heteroskedasticity
    Nonnormality
    Chapter 8: Modelling and Presentation of Curvilinear Effects
    Curvilinearity in the Linear Model Framework
    Nonlinear Transformations
    Polynomial Regression
    Regression Splines
    Nonparametric Regression
    Generalized Additive Models
    Chapter 9: Interaction Effects in Linear Models
    Understanding Interaction Effects
    Interactions Between Two Categorical Variables
    Interactions Between One Categorical Variable and One Quantitative Variable
    Interactions Between Two Continuous Variables
    Interaction Effects: Some Cautions and Recommendations
    Part C: The Generalized Linear Model and Extensions
    Chapter 10: Generalized Linear Models
    Basics of the Generalized Linear Model
    Maximum Likelihood Estimation
    Hypothesis tests and confidence intervals
    Assessing Model Fit
    Empirical Example: Using Poisson Regression to Predict Counts
    Understanding Effects of Variables
    Measuring Variable Importance
    Model Diagnostics
    Chapter 11: Categorical Dependent Variables
    Regression Models for Binary Outcomes
    Interpreting Effects in Logit and Probit Models
    Model Fit for Binary Regression Models
    Diagnostics Specific to Binary Regression Models
    Extending the Binary Regression Model - Ordered and Multinomial Models
    Chapter 12: Conclusions and Recommendations
    Choosing the Right Estimator
    Research Design and Measurement Issues
    Evaluating the Model
    Effective Presentation of Results