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Learn about ANOVA for repeated measures in SPSS with data from the World Development Indicators (2002-2012) / The Odum Institute.

By: Material type: TextPublisher: London : SAGE Publications Ltd., 2018Description: 1 online resource: illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9781526438034 (online resource) :
Subject(s): DDC classification:
  • 519.5
Online resources: This dataset example introduces readers to ANOVA for repeated measures. This technique allows researchers to test whether there are differences between three or more related groups of measurements. Hence, it is commonly used to study any change in the subjects from one time point to another, or to compare the effects of different treatments/conditions. This example uses a subset of data from the World Development Indicators from the World Bank. It examines any global change in the Gini index between the years 2002, 2007 and 2012. Results from an analysis like this could reveal global changes in the equality of wealth and inform economic and government policies.In this example, readers are introduced to the basic theory and assumptions underlying this technique, the type of questions this technique can be used to answer, and how to produce and report results. The sample dataset has been cleaned and organized to make this example easier to follow. Interested readers should read the full documentation for the dataset before using it for research (https://data.worldbank.org/data-catalog/world-development-indicators/).
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This dataset example introduces readers to ANOVA for repeated measures. This technique allows researchers to test whether there are differences between three or more related groups of measurements. Hence, it is commonly used to study any change in the subjects from one time point to another, or to compare the effects of different treatments/conditions. This example uses a subset of data from the World Development Indicators from the World Bank. It examines any global change in the Gini index between the years 2002, 2007 and 2012. Results from an analysis like this could reveal global changes in the equality of wealth and inform economic and government policies.In this example, readers are introduced to the basic theory and assumptions underlying this technique, the type of questions this technique can be used to answer, and how to produce and report results. The sample dataset has been cleaned and organized to make this example easier to follow. Interested readers should read the full documentation for the dataset before using it for research (https://data.worldbank.org/data-catalog/world-development-indicators/).

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