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Biostatistics is the branch of statistics that studies the use of statistical methods in medical and biological problems. Homework help on Biostatistics teaches and helps to investigate in all areas of Life Sciences where variability is not the exception but the rule. Our Biostatistics Homework Help Experts classify Statistics as descriptive when the results of the analysis are not intended to go beyond the data set, and inferential when the objective of the study is to derive the conclusions obtained from a larger data set.
Descriptive Statistics: Describe, analyze, and represent a group of data using numerical and graphical methods that summarize and present the information contained in them.
Inferential Statistics: Based on the calculation of probabilities and from sample data, it makes estimates, decisions, predictions, or other generalizations about a larger set of data. Its fundamental task is to make inferences about the population from a sample drawn from it. The analysis of a database will always start from simple techniques to summarize the data and present the results.
Based on these initial results, and depending on the study design and the pre-established hypotheses, statistical inference techniques will be applied that will allow conclusions to be drawn about the relationships between the variables studied.
Statistics is the discipline interested in the organization and summary of data, to obtain conclusions about the characteristics of a set of people or objects, when only a portion is available for study. Biostatistics is the branch of statistics that deals with problems posed within the science of life, such as biology or medicine. Doctors, Public Health Experts, Nurses, Kinesiologists, among others, need to know the principles that guide the application of statistical methods to the topics of their respective areas of knowledge because it is the objective, rational and mathematical method through which a scientific hypothesis can be tested.
That is why, to facilitate its study, it has been divided into four functions: sample design, sample size calculation, descriptive statistics, and analytical or inferential statistics. Considering that clinical research is carried out on a sample that must represent the study of a population, the data must be mathematically analyzed, using the appropriate statistical tests, so that scientifically valid conclusions can be drawn. So relevant is biostatistics that the health evidence is built on it.
Biostatistics has become a discipline, which has benefited both medicine and statistics in general. The growth of quantitative methods in the biomedical sciences has made this discipline a key element in areas such as epidemiology and clinical trials. In the field of epidemiology, its presence at all levels of an investigation: descriptive, relational, explanatory, predictive, and applicative, is evidenced from the formulation of the question to the analysis of the results that constitute the basis of the decision making and that can modify the health of both the individuals included in the study and those to whom the findings are generalized.
The development of drugs, new products, and technological procedures, requires the realization of clinical trials that are carried out following the principles of experimentation in human beings and the application of statistical methods aimed at demonstrating their effectiveness in the health problem under study.
Even though biostatistics frequently tends to be rejected by students, professionals, and researchers, they must become familiar with it due to the advantages it offers, whether in the search for continuous updating or in carrying out research projects. Most health research and clinical decisions are supported by statistical analysis. Therefore, it is essential to know basic elements of this discipline, descriptive and inferential statistics as well as making adequate use of statistical tests taking into account the conditions in which they can be applied.
On the other hand, it will allow them to critically read the scientific literature, identify the decisions and conclusions that lack a scientific and logical basis, better interpret the published results, and apply them in practice. On the contrary, the lack of sufficient statistical training could lead some researchers to their incorrect application or to limit their use to relatively simple and insufficient techniques to tackle and solve relevant problems.
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