Biostatistics, Biology tutorial

Introduction:

Biostatistics can be defined as the application of statistical methods or processes to the solution of biological problems. The biological problems of this definition are such arising in the fundamental biological sciences and also in such applied regions as the health-related sciences and the agricultural sciences. Biostatistics is as well termed as the biological statistics or biometry.

Biostatistics can as well be stated as the application of the mathematical tools employed in statistics to the fields of biological medicine and sciences.  Biostatistics is an emergent field having applications in most of the regions of biology comprising epidemiology, health sciences, medical sciences, educational research and ecological sciences.

Applications of biostatistics:

a) Public health, comprising epidemiology, health services research, ecological health, nutrition and healthcare policy and management.

b) Design and analysis of the clinical trials in medicine.

c) Evaluation of severity state of a patient having prognosis of outcome of a disease.

d) Population genetics and statistical genetics in order to link variation in genotype having a variation in the phenotype. This has been employed in agriculture to enhance crops and farm animals (that is, animal breeding). In biomedical research, this work can help in finding candidates for gene alleles which can cause or affect predisposition to disease in human genetics

e) Study of genomics data, for instance from microarray or proteomics experiments.

f) Ecology and ecological estimation.

g) Biological series analysis.

g) Biology systems for the gene network inference and pathways analysis.

History of Biostatistics:

The Statistics has grown via consecutive periods: era of censuses, era of the vital statistics, era of expressive statistics, era of analytic statistics and era of probability statistics. Earliest civilizations counted their populations for taxation and military reasons. The whole census were initially carried out in Sweden in the year 1749, US in 1790, Spain in 1798, England, Wales in 1801 and Canada in the year 1871. John Graunt is considered as the founder of the vital statistics. He examined London mortality data and as well laid the basics of the science of demography. William Farr began the modern processes of vital statistics registration. Pierre Charles Alexander Louis (1787-1872) proposed the numerical process in explaining medical facts quantitatively.

The nineteenth century (19th century) and early 20th centuries viewed lots of theoretical developments. Karl Pearson (1857-1936) proposed the mode, mean deviation, moments, coefficient of variation, measures of symmetry and kurtosis, the chi-square, symbol of the null hypothesis (H0), type 1 and type 11 errors, heteroscedacity and homoscedacity, and the theory of partial correlation. Sir Arnold Fisher (1890-1962) proposed variance, process for small samples, factorial designs, the null hypothesis, random allocation, ANOVA, relation among regression and ANOVA, and testing importance of the regression coefficient. Karl Pearson and RA Fisher build up contingency table analysis by employing the chi-square test. Adolph Quetelet builds up crucial statistics in its modern form and proposed the theory of the mean. KF Gauss (1777-1855) proposed the median, re-discovered the normal distribution that consists of independently been discovered prior to Pierre Simon Marquis de Laplace (1749-1827) and in the year 1733 by Abraham de Moivre (1667-1754). Sir Francis Galton employed the word 'normal' to signify to the curve, applied statistical methods to natural phenomena, explained regression and correlation. W.F. Sheppard proposed the standard normal curve in the year 1899. C Kremp described the first table of the area under the curve in the year 1799. J Neyman builds up the theory of confidence intervals in the year 1934. Charles Spearman (1863-1945) and Maurice George Kendall (1907-1983) proposed non-parametric tests.

The volume of statistical theory is probability theory as modern inferential statistics based on the probability theory. Christian Huygens (1629-1695) was the former one to publish on probability and games. Modern probability theory obliged a lot to the pioneers: Blaise Pascal (1623-1662), Pierre de Fermat (1601-1665), Jacques Bernoulli (1654-1705) and so on.

Limitations of Biostatistics:

A researcher begins with a substantive question which is formulated as a statistical question. Data is then gathered and is examined to reach a statistical conclusion. The statistical conclusion is employed with other knowledge to reach a substantive conclusion.

Statistics consists of quite a few limitations. It provides statistical and not substantive answers. The statistical conclusion signifies to groups and not individuals. It just summarizes but doesn't interpret data.

Statistics can be maltreated by selective presentation of desired outcomes. Calculation is not an end in itself. This is a tool which can be employed well or can be misused. A human should encompass a clear idea of what is needed of the computer and should train it accordingly. The human should as well be capable to intelligently understand the output from the computer.

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