Regression, ANOVA, and the General Linear Model: A Statistics Primer
Autor Peter W. Viken Limba Engleză Electronic book text – 31 mar 2013
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Specificații
ISBN-13: 9781483310336
ISBN-10: 1483310337
Pagini: 344
Dimensiuni: 187 x 232 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
ISBN-10: 1483310337
Pagini: 344
Dimensiuni: 187 x 232 mm
Ediția:1
Editura: SAGE Publications
Colecția Sage Publications, Inc
Locul publicării:Thousand Oaks, United States
Recenzii
“I
believe
that
when
students
are
taught
about
statistics
using
the
approach
of
this
text,
they
have
a
MUCH
deeper
understanding
and
appreciation
of
the
material.
It
is
really
fantastic.”
“The author does a really nice job of explaining the General Linear Model (GLM) by comparing it to hypothesis testing and showing [some of] its real-world applicability.”
“The text includes simple descriptions of complex mathematical concepts that are the foundation of statistics in the social sciences.”
“I think the book provides a nice step-by-step approach to understanding ANOVA and regression techniques. The author does an excellent job breaking down the different components of these statistical techniques while capturing the attention of the reader.”
“…the author really takes the readers step by step and makes the material easy to follow even for readers without extensive mathematics backgrounds.”
“The author does a really nice job of explaining the General Linear Model (GLM) by comparing it to hypothesis testing and showing [some of] its real-world applicability.”
“The text includes simple descriptions of complex mathematical concepts that are the foundation of statistics in the social sciences.”
“I think the book provides a nice step-by-step approach to understanding ANOVA and regression techniques. The author does an excellent job breaking down the different components of these statistical techniques while capturing the attention of the reader.”
“…the author really takes the readers step by step and makes the material easy to follow even for readers without extensive mathematics backgrounds.”
Cuprins
Chapter
1:
Introduction
Part I: Foundations of the General Linear Model
Chapter 2: Predicting Scores: The Mean and the Error of Prediction
Chapter 3: Bivariate Regression
Chapter 4: Model Comparison: The Simplest Model Versus a Regression Model
Part II: Fundamental Statistical Tests
Chapter 5: Correlation: Traditional and Regression Approaches
Chapter 6: T-test: Concepts and Traditional Approach
Chapter 7: Oneway Analysis of Variance (ANOVA): Traditional Approach
Chapter 8: T-test, ANOVA, and the Bivariate Regression Approach
Part III: Adding Complexity
Chapter 9: Model Comparison II: Multiple Regression
Chapter 10: Multiple Regression: When Predictors Interact
Chapter 11: Two-way ANOVA: Traditional Approach
Chapter 12: Two-way ANOVA: Model Comparison Approach
Chapter 13: One-way ANOVA with Three Groups: Traditional Approach
Chapter 14: ANOVA with Three Groups: Model Comparison Approach
Chapter 15: Two by Three ANOVA: Complex Categorical Models
Chapter 16: Two by Three ANOVA: Model Comparison Approach
Chapter 17: Analysis of Covariance (ANCOVA): Continuous and Categorical Predictors
Chapter 18: Repeated Measures
Chapter 19: Multiple Repeated Measures
Chapter 20: Mixed Between and Within Designs
Appendices
A: Research Designs
B: Variables, Distributions, & Statistical Assumptions
C: Sampling and Sample Sizes
D: Null Hypothesis, Statistical Decision-Making, & Statistical Power
Part I: Foundations of the General Linear Model
Chapter 2: Predicting Scores: The Mean and the Error of Prediction
Chapter 3: Bivariate Regression
Chapter 4: Model Comparison: The Simplest Model Versus a Regression Model
Part II: Fundamental Statistical Tests
Chapter 5: Correlation: Traditional and Regression Approaches
Chapter 6: T-test: Concepts and Traditional Approach
Chapter 7: Oneway Analysis of Variance (ANOVA): Traditional Approach
Chapter 8: T-test, ANOVA, and the Bivariate Regression Approach
Part III: Adding Complexity
Chapter 9: Model Comparison II: Multiple Regression
Chapter 10: Multiple Regression: When Predictors Interact
Chapter 11: Two-way ANOVA: Traditional Approach
Chapter 12: Two-way ANOVA: Model Comparison Approach
Chapter 13: One-way ANOVA with Three Groups: Traditional Approach
Chapter 14: ANOVA with Three Groups: Model Comparison Approach
Chapter 15: Two by Three ANOVA: Complex Categorical Models
Chapter 16: Two by Three ANOVA: Model Comparison Approach
Chapter 17: Analysis of Covariance (ANCOVA): Continuous and Categorical Predictors
Chapter 18: Repeated Measures
Chapter 19: Multiple Repeated Measures
Chapter 20: Mixed Between and Within Designs
Appendices
A: Research Designs
B: Variables, Distributions, & Statistical Assumptions
C: Sampling and Sample Sizes
D: Null Hypothesis, Statistical Decision-Making, & Statistical Power
Descriere
The
author
demonstrates
basic
statistical
concepts
from
two
different
perspectives,
giving
the
reader
a
conceptual
understanding
of
how
to
interpret
statistics
and
their
use