Importance of Statistics for Veterinary Medicine & Animal Science

Introduction

Importance of Statistics for Veterinary Medicine & Animal Science has a significant impact. Statistics, the study of knowledge processing, examination, presentation, and interpretation. Much of the early momentum for the statistics sector was provided by governmental needs for census data as well as information about a range of economic activities. At present, both theoretical and practical advances in statistics have been prompted by the need to translate the vast quantities of data available in many applied fields into usable knowledge (Sweeney et al. 2019). The importance of Statistics for Veterinary Medicine & Animal Science are discussed below:

Importance of Statistics

In determining the current position of per capita income, unemployment, population growth rate, housing, education, medical services, etc in a country, statistics play an important role. In almost every field, such as Business, manufacturing, commerce, trade, physics, chemistry, economics, mathematics, biology, botany, psychology, astronomy, etc., statistics now hold a central role, so the application of statistics is very large. Statistical approaches are used for two main purposes. The first is to classify the individual sample of data under review. The second is to calculate the magnitude of a discrepancy between that sample and some other actual sample or some potentially expected value. The two purposes of description and verification of meaning are not distinct from each other but far from being the same. Importance of Statistics for Veterinary Medicine & Animal Science has also a significant impact on research Purpose also,

List of Statistics’ Implementation Fields

Statistics is the science of mathematics that includes data collecting, analysis, and interpretation. In order to apply statistics and techniques to different fields, a variety of specialties have evolved. Certain subjects have “statistical” in their name, but they refer to probability distribution manipulations rather than statistical analysis.

Actuarial science:

The discipline that applies quantitative and statistical methods to determine risk in the insurance and finance industries is actuarial science.

Astrostatistics:

The discipline that applies statistical analysis to astronomical data comprehension is astrostatistics.

Biostatistics:

Biostatistics is a branch of biology that by statistical analysis, studies biological processes and findings, and involves medical statistics.

Business Analytics:

Business analytics is a rapidly evolving business process that uses statistical techniques to gain new insights and understanding of business results and opportunities in data sets (often very large).

Chemometrics:

Chemometrics is the science of relating, by applying mathematical or statistical methods, measurements made on a chemical system or process to the state of the system.

Demography:

The comparative analysis of all populations is demography. It can be a very general science that can be applied to any form of dynamic population, that is, evolving over time or space.

Econometrics:

Econometrics is a branch of economics that applies the empirical study of economic theories and relationships to statistical methods.

Environmental Statistics:

The application of statistical methods to environmental science is Environmental Statistics. As well as studies of plant and animal species, weather, atmosphere, air, and water quality are included.

Epidemiology:

The study of factors influencing the health and disease of populations is epidemiology and serves as the basis and rationale of initiatives in the interest of public health and preventive medicine.

Geostatistics:

Geostatistics is a geography division that analyzes data from fields such as petroleum geology, hydrogeology, hydrology, meteorology, oceanography, geochemistry, and geography.

Jurimetrics:

The application of probability and statistics to legislation is Jurimetrics.

Machine learning:

The subfield of computer science that formulates algorithms to make predictions from data is machine learning.

Operational Research:

Operational research (or operational research) is an interdisciplinary branch of applied mathematics and formal science that uses techniques such as mathematical modeling, statistics, and algorithms to solve complex problems optimally or nearly optimally.

Population Ecology:

Population ecology is a sub-field of ecology that discusses the dynamics of populations of organisms and how they communicate with the environment.

Psychometrics:

The theory and methodology of educational and psychological assessment of awareness, skills, behaviors, and characteristics of personality is psychometrics.

Quality control (QC):

Quality management reviews the variables involved in production and manufacturing; a statistical sampling of product products may be used to help in process control decisions or in approving deliveries.

Quantitative psychology:

The science of scientifically describing and modifying mental processes and behaviors in humans is quantitative psychology.

Reliability engineering:

Reliability engineering is the analysis of a device or component’s ability to perform its necessary functions for a given period of time under stated conditions.

Statistical finance:

Statistical finance, a field of economic physics, is an empirical attempt to move finance from its normative origins to a positivist context, using statistical physics examples with a focus on financial markets’ emerging or collective properties.

Statistical mechanics:

Statistical mechanics is the application to the field of mechanics of probability theory, which involves mathematical instruments for dealing with large populations, concerned with the motion of particles or objects when subjected to force.

Statistical physics:

One of the basic theories of physics is statistical physics, which uses the principles of probability theory in solving physical problems.

Signal processing:

In order to perform signal processing operations, statistical signal processing utilizes the statistical properties of signals.

Statistical thermodynamics:

Statistical thermodynamics uses probability theory to analyze the microscopic actions of thermodynamic systems and offers a molecular understanding of thermodynamic quantities such as function, heat, free energy, and entropy. Statistical signal processing uses the statistical characteristics of signals to conduct tasks of signal processing.

The analysis of the microscopic actions of thermodynamic systems using probability theory is statistical thermodynamics and offers a molecular understanding of thermodynamic quantities such as work, heat, free energy, and entropy.

The study of livestock, diseases & disorders that occur in different animals are successfully treated by veterinary medicine and animal sciences.

For two main reasons, statistical techniques are employed. The first is to identify the individual data sample under review. The second is to measure the importance of a difference between that sample and some other real sample or some value that is theoretically predicted. The two purposes of definition and significance checking are not independent of each other but far from being the same (Lush, J. L. 1933).

Veterinary Medicine & Animal Science

Veterinary medicine is the branch of medicine that deals with illness, deficiency, injury prevention, control, diagnosis, and care in animals. It also deals with animal rearing, husbandry, breeding, nutrition analysis, and product development in addition to this. The field of veterinary medicine is broad and includes all types of animals, both domesticated and wild, with a wide variety of conditions that may affect various species. Veterinary medicine, both with and without clinical guidance, is commonly practiced. Veterinary science promotes human health through zoonotic disease detection and control (infectious diseases transmitted from non-human animals to humans), food protection, and, indirectly, basic medical research through human applications. Veterinarians are normally obliged, ethically, to look after animal health. A veterinarian’s job is to diagnose, treat, and help keep animals healthy and secure.

“Studying the biology of animals that are under the control of humankind” can also be defined as farm animal manufacturing and management. The degree was historically referred to as animal husbandry and the animals examined were species of livestock, such as cattle, sheep, pigs, poultry, and horses. Today, in addition, to including domestic animals such as dogs and cats, and many exotic species, courses available now look at a much wider area. At a variety of colleges and universities, degrees in animal science are offered. The Animal Science program usually offers not only a solid foundation in science but also realistic experience working with animals on campus-based farms.

Veterinary physicians, students, and fellow researchers have been a fantastic source of knowledge for the Journal of Veterinary Medicine and Animal Sciences. In adding a more scientific basis to its practice, veterinary medicine approaches human medicine under the term evidence-based veterinary medicine (EBVM). To underpin clinical decisions, veterinarians are progressing towards reliance on scientific studies. The EBVM means that clinical decision is based not only on clinical knowledge but also on the appropriate and reliable research studies available on the conditions. Evidence comes with varying reliability so veterinarians face the challenge of choosing the best evidence and objectively testing it. The clinician must know and be able to use rigorous methods to determine, what information is important and how to access this data. This usually includes an understanding of statistical analysis concepts and techniques. Scientific evidence based on statistical analysis is used not only in clinical disease management but also in the development and performance aspects of animal science. There are a growing number of independent consulting services in animal sciences that will assess livestock productivity for the purpose of health monitoring and maintenance. These consultancy firms should always be worried about the consistency of data and the precision of statistical statistics.

For those interested in dealing with animals, Animal Science is an additional field of research to Veterinary Medicine. In an agricultural, Para-veterinary, laboratory, or wildlife background, it includes research on the structure and function of animals, their management, and welfare. Animal science also requires the application of scientific expertise and concepts to the understanding of the production, processing, and marketing of animal products and the management and protection of our natural resources, including native and endangered species. A degree in this field offers good prospects for employment in the animal and biomedical research industries.

Epidemiology is the study of diseases and factors that influence their occurrence in populations. Management of animal infectious diseases in livestock is also a problem. Veterinary epidemiology requires investigation and evaluation of other health-related incidents. In any scenario, statistical assessment establishes advice and effective regulations, says Dr. Richard Branson, professor of veterinary epidemiology at the University of Sheffield. Veterinary epidemiology is mainly concerned with the study, through veterinary epidemiology, of diseases or disorders in animals that affect certain populations or patterns of disease conditions within the population of animals affected, the location of affected animals, and the patterns of disease over time.

Through the detection and control of zoonotic infectious diseases transmitted from non-human animals to humans, food safety, and indirectly through human applications, veterinary science promotes human health through basic medical research.

They also help sustain the supply of food by monitoring and caring for animal health and mental health by keeping pets safe and long-lived. Depending on the nature of work, veterinary scientists frequently collaborate with epidemiologists, other health, or natural scientists. Veterinarians are normally obliged, ethically, to look after animal health.

Important Aspects of Veterinary Medicine & Animal Science

The subject’s mathematical foundation creates a lot of confusion, and the theoretical approach is foreign.

Statistical analysis-based empirical evidence is used not only in the treatment of human disorders but also in the developmental and performance aspects of animal science. Using statistical analysis, many of these studies involve tracking and inferencing animal populations.
There are a growing number of independent animal health science diagnostic facilities that will test samples for health monitoring and maintenance purposes. Those providing such laboratory facilities must always be concerned with quality control and diagnostic measurement accuracy and must be in a position to provide specific guidance about how to interpret the results obtained in their laboratories(Petrie et al ,2013).
The statistical architecture eliminates bias and improves generalize ability, and sufficient analysis leads to acceptable conclusions. As veterinarians are responsible for the medical care of their patients, it is also their responsibility to recognize the treatment-related inferences made in reports.
Statistics to educate and provide information to the scientific community, animal welfare groups, and the general public on the implementation of policies on animal use in scientific work.

How Statistics can be used for veterinary medicine & animal science development

Something is expected to apply statistical techniques that tend to be groups of animals for veterinary studies before even thinking of a t-test or a p-value. For all that comes next, it is entirely important how these groups are put together and tested, and if care is not taken, bias will be applied that will nullify any apparent findings(AAH, 2020).
The scientific literature published is full of studies that employ statistical procedures. Look at some of the related scientific articles and note that the number of references is made to mean ± SEM (standard error of the mean), statistical significance, P-values or t-tests or Chi-squared analysis or variance analysis, or multiple regression analysis. The data is provided in the normal short form and you are left to acknowledge the statistics without working knowledge. In reality, many practitioners can now gather their own findings and summarize them for the benefit of their colleagues with the advent of computer-assisted data handling; to do so they need the benefit of statistical insights (Petrie et al,2013).
When looking at charts or graphs, veterinarians use statistics. Another case is when a veterinarian reads an outcome for a pet. Percentages, ratios, ratios, conversions, and a lot of what they learned to get into a veterinary school are used during work or everyday vets.
The method by which one draws conclusions about a population from the findings found in a sample taken from that population is statistical inference. The statistical inference has two categories: estimation and checking of hypotheses. Estimation is concerned with calculating the real value of an unknown population parameter, while the testing of hypotheses is concerned with settling on the hypothesized value of an unknown population parameter. In either case, we need some context first on something called the typical mistake.

The problems that veterinarians are actually faced

Veterinarians and animal science practitioners need to be aware of the appropriate statistical procedures in order to perform their proper roles. Nevertheless, it is difficult for them to interpret data because they have had little chance to get practical training. For them, there is often a tendency to hesitate exclusively to study statistics. Many veterinary and animal science students do not sense the need for statistical analysis to be obtained. However, in professional life, there are many examples of the value of statistics (Satoshi Sekiguchi et al,2018).

The way the problem can be solved

Statistics courses should be included in the first year for veterinary departments. The lab class needs to be increased for statistics & the basic concept of statistics should be kept clear. The basics of statistical analysis need to be learned well for veterinary research. If necessary, training should be started.

Conclusion

In the office, demands for research, statistics are changing. They have no hope of gaining a practical education, however. It is hard to interpret data from veterinarians and research employees. A practical training course in veterinary medicine and Statistics on zoology and the postgraduate education system must be established. Thus, Importance of Statistics for Veterinary Medicine & Animal Science can not be denied.

References:

Petrie, A., & Watson, P. (2013). Statistics for veterinary and animal science. John Wiley & Sons.

Sweeney, D. J., Williams, T. A., & Anderson, D. R. (2019). Statistics-Experimental design. en. URL: https://www. britannica. com/science/statistics (visited on 04/30/2019).

Satoshi Sekiguchi, Yosuke Sasaki, Ryoko Uemura, Masuo Sueyoshi, Yoshinori Fujii

In M. A. Sorto, A. White, & L. Guyot (Eds.), Looking back, looking forward. Proceedings of the Tenth International Conference on Teaching Statistics (ICOTS10, July, 2018), Kyoto, Japan.Voorburg, The Netherlands: International Statistical Institute.

Lush, J. L. (1933). The use of statistical methods in animal husbandry. Journal of Animal Science, 1933(1), 15-19.

AAH (2020, July 10) Retrieved from www.avactaanimalhealth.com/2019/07/10/understanding-veterinary-papers-a-data-and-statistics-perspective-part-2

Animal Science”. The University of Reading. Retrieved 2009-04-15.

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