Primer of Biostatistics Term Paper Example | Topics and Well Written Essays - 2000 words

Primer of Biostatistics - Term Paper physical exertionDuring data analysis, quite often, either of descriptive statistics or inferential statistics methodologies is employed. Descriptive statistics (which unlike inferential statistics is non developed on the basis of probability theory) basically refers to the discipline of quantitatively describing the main features of a disposition of data while inferential statistics on the other hand denotes the process of arriving at conclusions from data undefendable to random or sampling variations (such as observational errors) (Graham, pg.40). Statistics is a wide field of study, probably star of the broadest disciplines available, with a plethora of applications too. The topic of Fields of Application of Statistics is a rich topic in itself and unity that sparks a lot of interest both to scholars and professions globally. Some of the sub-topics herein include actuarial science, astro-statistics, business analytics, chemo-metrics, demo graphy, econometrics, environmental statistics, epidemiology, geo statistics, operations enquiry, population ecology, statistical thermodynamics, and biostatistics and so on (Graham, pg.82). This paper deals with the biostatistics aspect of statistics. Biostatistics, commonly referred to as biometry, is the manipulation of statistics in a wide range of topics in biology. Biostatistics deals with the design of biological experiments (such as in medicine, agriculture, pharmacy, fishery, etc), the collection, summarisation and analysis of collected information from the experiments, followed by the interpretation of, and interference from, the results. Biostatistics is a combination of mathematics and reasoning, it considers how research questions are generated, studies are designed, data are collected and results interpreted. If the samples one takes are representative of the population of interest, they get out provide good estimates concerning the overall population (Hubert).