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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Analyzing Quantitative Data

Analyzing Quantitative Data
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Author(s): Sema A. Kalaian (Eastern Michigan University, USA) and Rafa M. Kasim (Indiana Tech University, USA)
Copyright: 2016
Pages: 16
Source title: Mixed Methods Research for Improved Scientific Study
Source Author(s)/Editor(s): Mette Lise Baran (Cardinal Stritch University, USA) and Janice Elisabeth Jones (Cardinal Stritch University, USA)
DOI: 10.4018/978-1-5225-0007-0.ch008


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The main purpose of this chapter is to present a conceptual and practical overview of some of the basic and advanced statistical tools for analyzing quantitative data. Analyzing quantitative data involves two broad analytical methods that serve two main purposes, which are descriptive and inferential statistical methods. The chapter covers both descriptive and inferential quantitative methods. It covers some of the descriptive statistical methods such as mean, median, mode, variance, standard deviation, and graphical methods (e.g., histograms). It also covers inferential statistical methods such as correlation, simple regression, multiple regression, t-test for two independent samples, t-test for two dependent samples, and analysis of variance (ANOVA).

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