Abstract
We finally approach the third and final leg of our “three-legged” stool, particularly data analysis. In the remaining chapters of the first half of the book, we will look at inferential and descriptive statistics, but for now, we direct our attention to the latter. Unlike inferential statistics, descriptive statistics does not attempt to make inferences from a sample to the whole population. As its name suggests, descriptive statistics describes, summarizes, or presents the sample and the observations that have been made based on the data collected in an organized manner.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
A scientific law implies absolute truth without the possibility of contradiction, whereas a scientific theory implies general agreement among scientists that have yet to uncover substantiating evidence for refutation.
- 2.
Heisenberg outlined the inverse relationship shared between the position and momentum of an electron, such that the moment one attempts to locate the precise position of an electron, the electron has already traversed elsewhere.
- 3.
Often referred to as relative frequency.
- 4.
Again, the final cumulative frequency percent should ideally be equal to 100% but can realistically be anywhere between 99% and 101% as there may be errors in rounding.
- 5.
This is contingent on their being an odd number of observations. If there are an even number of observations and the middle two observations are not identical, then the median cannot be calculated (see median definition and its contingencies above).
- 6.
The order in which we calculate is parentheses>exponents>multiplication>division>addition>subtraction; the acronym for which is commonly known as PEMDAS.
- 7.
- 8.
Depending on the size of data, these measures must not necessarily be exactly equal to one another but relatively close in order for a normal distribution to be observed.
- 9.
Notice, now, how the measures of central tendency are essentially a description of the distribution of data. The calculated mean tends to fall in the center, the median—by definition—is in the middle, and the mode is the observation that occurs most frequently which is the highest bar in a frequency polygon and later the peak in the normal distribution.
- 10.
This is not to make normal distributions exclusive to populations. Sample data may very well be normally distributed as well, the reasoning we save for the next chapter under the central limit theorem.
- 11.
Colloquially, we often use or hear the usage of phrases such as: “I am 150% sure!”—unfortunately, that is impossible.
- 12.
Bibliography
Klute R. Stylised atom with three Bohr model orbits and stylised nucleus [Stylised atom. Blue dots are electrons, red dots are protons and black dots are neutrons]. 2007. https://commons.wikimedia.org/wiki/File:Stylised_atom_with_three_Bohr_model_orbits_and_stylised_nucleus.svg.
Kolmogorov AN. The theory of probability. In: Alexandrov, A. D., Kolmogorov, A. N., Lavrent'ev, M. A., eds., Mathematics, Its Content, Methods, and Meaning, Vol. 2. MIT Press, Cambridge, MA 1965.
Walker JS. Figure 8: Electron cloud model for the 1s orbital. [Digital image]. 2018. http://thebiologyprimer.com/atoms-and-molecules/.
Recommended Reading
Perkins J, Wang D. A comparison of Bayesian and frequentist statistics as applied in a simple repeated measures example. J Mod Appl Stat Methods. 2004;3(1):24. https://doi.org/10.22237/jmasm/1083371040. Available at: http://digitalcommons.wayne.edu/jmasm/vol3/iss1/24
Raue A, Kreutz C, Theis FJ, Timmer J. Joining forces of Bayesian and frequentist methodology: a study for inference in the presence of non-identifiability. Philos Trans A Math Phys Eng Sci. 2013;371(1984):20, 110, 544. https://doi.org/10.1098/rsta.2011.0544.
Sanogo M, Abatih E, Saegerman C. Bayesian versus frequentist methods for estimating true prevalence of disease and diagnostic test performance. Vet J. 2014;202(2):204–7. https://doi.org/10.1016/j.tvjl.2014.08.002.
Author information
Authors and Affiliations
1 Electronic Supplementary Materials
Frequency tables. Reprint courtesy of International Business Machines Corporation, © International Business Machines Corporation (MOV 79842 kb)
Graphing. Reprint courtesy of International Business Machines Corporation, © International Business Machines Corporation (MOV 75639 kb)
Rights and permissions
Copyright information
© 2018 Springer-Verlag GmbH Germany, part of Springer Nature
About this chapter
Cite this chapter
Khakshooy, A.M., Chiappelli, F. (2018). Descriptive Statistics. In: Practical Biostatistics in Translational Healthcare. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-57437-9_4
Download citation
DOI: https://doi.org/10.1007/978-3-662-57437-9_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-57435-5
Online ISBN: 978-3-662-57437-9
eBook Packages: MedicineMedicine (R0)