Chapter 2
Biostatistics: Introduction
Chapter 2
Biostatistics: Introduction
Biostatistics is the application of statistical methods to analyze data by conducting experiments to gather evidence and drawing conclusions based on …
In biostatistics, data refers to the collected observations that are subject to analysis. Data can be parametric or nonparametric.
Nonparametric data …
Measures of central tendency are descriptive statistical tools that describe the average or center of a data set.
These include mean, median, mode, and …
Measures of variability are vital in biostatistics for describing a dataset's dispersions and highlighting deviations between individual data points.
…
A hypothesis is a proposed explanation or assumption about a population parameter that serves as the basis for testing and analysis.
The null hypothesis, …
A hypothesis test starts with the assumption that the null hypothesis is true.
Two types of errors can occur in a hypothesis test. Type I error is the …
ANOVA, or Analysis of Variance, analyzes parametric statistical data by comparing means among multiple groups to determine their statistical …
The Student t-test examines if there is a significant difference between the means of two groups.
It is suitable for data that follows a normal …
Parametric statistical methods, like the Student t-test or goodness-of-fit test, assume that data follows a specific distribution, enabling robust …
Biopharmaceutical studies aim to study drug delivery and improved therapies using interdisciplinary knowledge.
Non-controlled studies, often used for …
Statistical learning, a fundamental skill to extract regularities in the environment, is often considered a core supporting mechanism of the first …
Starch from all plant sources are made up of granules in a range of sizes and shapes having different occurrence frequencies, i.e., exhibiting a size and …
The mustard aphid (L. erysimi) is a pest that infests various cruciferous crops and transmits plant viruses. To achieve eco-friendly pest management, …