# Quantitative Methods and Analysis

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## Abstract

In this chapter the different types of data that you may come across in quantitative research are explored. How data might be first described using various descriptive statistics is addressed before looking at which statistical tool is most appropriate to use and why. The distribution of data, particularly normal distribution curve that helps in the choice of both descriptive statistics and the inferential statistical test is discussed. The two forms of hypotheses, alternate and null, are introduced as well as probability levels and means of establishing whether the data are normally distributed or not. Statistical package for social sciences (SPSS) printouts of some of the more commonly used tests described in the chapter are included to show how to interpret data in order to come to the correct conclusion regarding reporting of the findings.

## Keywords

Normal Probability Statistical test Descriptive Inferential SPSS## Reference

- 1.Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1988.Google Scholar

## Further Reading

- Altman DG. Practical statistics for medical research. London: Chapman & Hall; 2018.Google Scholar
- Campbell MJ. Statistics at square two. Understanding modern statistical applications in medicine. 2nd ed. Oxford: Wiley-Blackwell; 2006.CrossRefGoogle Scholar
- Campbell MJ, Swinscow TDV. Statistics at square one. 11th ed. Oxford: Wiley-Blackwell; 2009.Google Scholar
- Claude CS, Longo G. The Deluge of spurious correlations in big data. Found Sci. 2017;22(3):595–612.CrossRefGoogle Scholar
- Miles J, Shevlin M. Applying regression and correlation: a guide for students and researchers. London: Sage; 2001.Google Scholar