Performing a parametric statistical analysis requires the justification of a number of necessary assumptions. If assumptions are not justified research findings are inaccurate and in question. What happens when assumptions are not or cannot be addressed? When a certain statistic has no known sampling distribution what can a researcher do for statistical inference? Options are available for answering these questions and conducting valid research. This paper provides various numerical approximation techniques that can be used to analyze data and make inferences about populations from samples. The application of confidence intervals to inferential statistics is addressed. The analysis of data that is parametric as well as nonparametric is discussed. Bootstrapping analysis for inferential statistics is shown with the application of the Index Function and the use of macros and the Data Analysis Toolpak on the EXCEL spreadsheet. A variety of interesting observations are described.
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Rochowicz, John A. Jr
Bootstrapping Analysis, Inferential Statistics and EXCEL,
Spreadsheets in Education (eJSiE):
3, Article 4.
Available at: http://epublications.bond.edu.au/ejsie/vol4/iss3/4