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What is Biostatistics?
Biostatistics is the study which integrates biological sciences and statistics. Statistical methods are applied in various biological sciences which include biological laboratory experiments, medical research, health services, epidemiology, etc. Statistics is one of the best studies which can be applied in biological science for collection, summarization and analysis of data. Statistical application in biological sciences has had an immense impact in how genes studied.
History of Biostatistics
The history of biostatistics can be traced back to the 18th century, when the English physician and statistician John Graunt published a landmark study on mortality rates in London. Over the next century, other notable figures in the field of statistics, including Pierre-Simon Laplace and Carl Friedrich Gauss, made important contributions to the development of statistical theory and methods. However, it was not until the late 19th century that biostatistics began to emerge as a distinct field.
One of the earliest pioneers of biostatistics was the British epidemiologist and statistician Major Greenwood, who published influential studies on infectious disease and mortality rates in the early 20th century.
During the mid-20th century, advances in technology and computing enabled the development of more complex statistical models and methods, such as linear regression, logistic regression, and survival analysis. These methods were applied to a wide range of biological and medical problems, from clinical trials and epidemiological studies to genetic research and environmental health.
In the latter half of the 20th century, the field of biostatistics continued to evolve, with the development of new statistical methods, such as hierarchical models, Bayesian methods, and machine learning. Today, biostatistics is a thriving field with applications in many areas of biological and medical research, including genomics, personalized medicine, and public health.
Types of Biostatistics Data
There are two main types of data in biostatistics: categorical and continuous.
- Categorical data: Categorical data are data that can be grouped into distinct categories or classes based on a qualitative characteristic. Examples of categorical data include gender (male or female), blood type (A, B, AB, or O), and disease status (present or absent). Categorical data can be further classified as nominal (unordered categories) or ordinal (ordered categories).
- Continuous data: Continuous data are data that can take on any value within a certain range. Examples of continuous data include height, weight, blood pressure, and age. Continuous data can be further classified as interval (equal units of measurement with no true zero point) or ratio (equal units of measurement with a true zero point).
In addition to these two main types of data, biostatistics also deals with missing data, outliers, and skewed data, which can all impact statistical analyses and must be carefully considered when interpreting results.
Branches of Biostatistics
The field of biostatistics is broad and encompasses several different branches, each with its own focus and applications. Some of the main branches of biostatistics include:
- Descriptive statistics: Descriptive statistics involves the use of numerical and graphical techniques to summarize and describe the features of a dataset.
- Inferential statistics: Inferential statistics involves making inferences and predictions about a population based on a sample of data. This includes hypothesis testing, confidence intervals, and regression analysis.
- Survival analysis: Survival analysis is a branch of biostatistics that deals with the analysis of time-to-event data, such as time until death or time until a disease occurs.
- Longitudinal data analysis: Longitudinal data analysis is the analysis of data collected over time from the same individual or group of individuals. This includes techniques such as mixed-effects models and repeated measures analysis.
- Spatial statistics: Spatial statistics is the analysis of data that has a spatial component, such as geographic data or data collected from different locations in a study area.
- Bayesian statistics: Bayesian statistics is a statistical approach that involves the use of prior knowledge and subjective beliefs to update probabilities and make inferences about a population.
These branches of biostatistics are often applied in a variety of fields, including medicine, public health, environmental science, genetics, and epidemiology.
Some of the areas where statistics is applied in biology include Public health (epidemiology, health services, nutrition, environmental health); Design and analysis of clinical trials in medicine; Study of Human and Population Genetics; Ecology and Ecological Forecasting; Biological sequence analysis, etc.
Some of the topics covered under Biostatistics include
- Biostatistical Design of Medical Studies
- Descriptive Statistics
- Statistical Inference: Populations and Samples
- Biometry
- Parametric Test
- Probability
- Discrete Probability Distributions and Continuous Probability Distributions
- Estimation
- Hypothesis Testing: One Sample Inference, Categorical Data, Person-Time Data
- Nonparametric Methods
- Regression and Correlation Methods
- Multisample Inference
- Design and Analysis Techniques for Epidemiologic Studies
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