Keywords
statistical analysis; sample size; power; t-test; anova; chi-square; regression
Disciplines
Applied Statistics | Biostatistics | Statistical Methodology
Abstract
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power. Variable types and definitions are included to clarify necessities for how the analysis will be interpreted. Categorical and quantitative variable types are defined, as well as response and predictor variables. Statistical tests described include t-tests, ANOVA and chi-square tests. Multiple regression is also explored for both logistic and linear regression. Finally, the most common statistics produced by these methods are explored.
Recommended Citation
Vandever, Christian
(2020)
"Introduction to Research Statistical Analysis: An Overview of the Basics,"
HCA Healthcare Journal of Medicine: Vol. 1:
Iss.
2, Article 4.
DOI: 10.36518/2689-0216.1062
Available at:
https://scholarlycommons.hcahealthcare.com/hcahealthcarejournal/vol1/iss2/4
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