Table of Contents

## Introduction

In biology, researchers, like students like you, study how living organisms work internally. Since biology is the study of all living things, scientists in this field have enough land to cover it. To help us understand our world and ourselves a little better, these biologists collect data. Their study can vary from recording sound files from bird calls in the forest to measuring the growth of cancer cells in the laboratory.

Without a statistical analysis, all the data collected by biology would not have a particular meaning. Biological statistics tests perform a series of tasks, including measuring correlations, comparing mean variables and predicting variability. Types of data tests the types you use include Chi-square, t-tests, onova, regression tests and more. Due to the role of biology statistics, you should take a series of courses in biology statistics if you wish to obtain a specialization in biology.

## The Role of Statistics

The role of statistical science in biology is biostatistics and biometry. Biostatistics is the branch of the science of statistics pertaining to statistical methods to apliksai issues in the field of biology and medicine. In biology, biostatistics used to designing experimental biology, collecting data and analyzing data. Biostatistics also introduce a statistical calculation of life as a life test data analysis is a statistical technique that is useful to perform testing of duration or reliability of a component or the measurement of the length of the durability of the life of the patient in the treatment of disease. Biometrics is often used to solve biological problems by implement statistical methods. Biometrics derived from two Greek words bio means life and metron means calculation. In addition, biometrics is a technology that demonstrates the integrity of a person using the organization’s resources.

## Importance of Statistics

Statistical tests used in biology provide scientists with information on processes that are too large, too microscopic or too many to be analyzed in other ways. The main role of statistics in biology is to verify the hypotheses. However, other statistical tests are used in biology to help prepare experiments and interpret the results.

While the study of biology focuses on living organisms, statistical analyzes provide information on many biological processes. Basic statistical concepts help biologists to correctly prepare experiments, validate results and interpret them correctly. Many biology courses in the study require a course in biostatistics that covers concepts such as randomized trials, hypothesis testing and the use of statistical programs.

## Uses of Statistcs in Biology

### Establishing Sample Size

An important part of any biological experiment is the right choice of samples and the right test number. A basic mathematical introduction provides an understanding of the mathematical randomness and the law of large numbers. For example, when investigating whether insects prefer to eat American elm leaves or Princeton elm leaves, using a poorly selected sample on both types of leaves helps control the mix. For example, choosing a small amount of American elm leaves, if they all come from the same tree, would cause the tree to be filled differently by insects, and this would distort the results. However, selecting hundreds of leaves from a random sample of trees reduces this type of error.

### Hypothesis Testing

When performing experiments with a large sample, the biologist must confirm that the conclusion is statistically significant. One of those tests may include checking whether smoking is withdrawing the cancer. By examining the pathways of two groups – one who smokes and one who is not – a biologist can find that smokers were more likely to have cancer. Methods, however, indicate the center of the distribution of data, and hypothesis testing involves testing the distribution of that distribution. If the data is aggregated too close to the definition, the mean value is a reliable indicator; the more information is disseminated, the less expressive it becomes in the process and should be considered in that context.

### Interpreting Data Analyses

At the end of an experiment or observation, biologists need statistics to draw the right conclusions. For example, comparing the data of two groups of plants – one watered and the other – may lead to incorrect conclusions. For example, a biologist may record the average height of these two plants and conclude that the watered plants were growing tall. However, this does not account for other statistical measures such as variance. Anhydrous plants may have grown to a low height on average, but their height may vary greatly Replicas are key data that is passed on to the conclusion

### Statistical Software

Extremely large data sets cannot be processed manually. In many biological settings, such as those in ecology that use large sample sizes, the use of statistical software makes data processing easier. Data programs include Stata; Statistical Analysis System, or SAS; most introductory statistics use software products that can be incorporated into learning programming languages.

## Biologists Use Statistics

Other statistical comments can help in selecting the sample size or which organisms you have studied in the group. Although it may seem that selecting studies in a group will undoubtedly give you the best possible analysis group, random samples may accidentally produce samples that do not occur naturally without a sample group. Biologists are careful to use statistical techniques to help with samples to keep their results clean.

### What types of statistical tests do biologists use?

The basic types of statistical tests used in biology fall into four basic categories: correlation, means of comparison, regression and heterogeneity. The correlation tests measure how two or more variables are involved. Compare means of measuring the difference between two or more variables or data sets. If a variable in a change is able to predict another variable and non-parametric tests are used, then the datasets do not meet the requirements of parametric analysis tests, and then they can be analyzed.

### How do biologists explain data?

Most biological experiments require interpretation of very long or very complex data to be analyzed by scientists manually. To perform many mathematical tests used in biology, researchers used specialized equipment in the software and mathematical field of the laboratory for data processing. When analyzing the data in the lab, researchers put the software to process the data can be used. Three programs are usually used for this purpose in the biology lab system is statistical analysis, statistical products and solutions and services Strat. Exercise is often needed for specific use computer programs, including preparation program in the primary. Students who advanced to the show after a biological graduate should expect a special on one or more of the computer program. In some cases, such as field studies of Vail Dorsal Finn Marks, biologists rely on observational and descriptive techniques for data collection. In such cases, descriptive observations are often combined with statistics to provide a more complete understanding of the subject being studied.

## Conclusion

Biology uses theory of statistics and applies to the life and health sciences. The experts in statistical science using their specific statistics approaches have helped to understand a variety of Diseases such as diabetes, cancer, obesity, heart disease, AIDS, and other diseases. Institutions related to biostatistics should organize basic and advanced activities. courses, certificate courses, diplomas program, diplomas programs etc and other opportunities for students to use this knowledge and methods later various sectors of employment in industry, government, life science, computer science, medicine, public health, education, teaching, research and surveys. Statisticians are the people who matter most to them Establish programs, organizations and Institutes in the fields of medicine and biology.