Biostatistics Introduction Quiz

Biostatistics Introduction

• Biostatistics applies statistical methods to biological, medical, and health studies.
• Statistical methods involve collecting, analyzing, interpreting, and presenting data.
• Biological measurements can be quantitative (e.g., height, weight, disease prevalence) or qualitative (e.g., gender, blood type).

Types of Biological Data

• Qualitative data is non-numeric (e.g., gender, blood type).
• Quantitative data is numeric and can be further categorized into:
  • Discrete data: Countable values (e.g., number of cells).
  • Continuous data: Measurable values (e.g., height, temperature).

Measures of Central Tendency

• Mean: The average of all data values. Formula: Mean = Σx / n, where Σx = sum of all values, and n = number of observations.
• Median: The middle value in an ordered dataset. If 'n' is odd, it's the middle value; if even, it's the average of the two middle values.
• Mode: The most frequently occurring value in a dataset.

Standard Deviation (SD)

• Standard Deviation (SD) measures data dispersion around the mean.

Data Collection

• Primary data is collected directly by researchers through experiments, surveys, or observations.
• Secondary data is previously collected data, found in publications or databases.

Sampling and Sampling Design

• Sampling is selecting a subset (sample) from a population for study.
• Types of Sampling:
  • Random sampling: Every individual has an equal chance of selection.
  • Stratified sampling: Population divided into subgroups, and samples are taken proportionally.
  • Systematic sampling: Selecting every nth individual from a list.
  • Cluster sampling: Dividing the population into clusters and sampling entire clusters.

Classification and Tabulation

• Classification: Organizing data into categories or classes based on characteristics.
• Tabulation: Presenting classified data in a systematic table format for analysis.

Types of Representation

• Textual representation: Describes data in words.
• Tabular representation: Organizes data into rows and columns.
• Graphical representation: Presents data visually for easier interpretation.

Graphical Biodiagrams

• Bar diagrams: Used for comparing discrete data.
• Pie charts: Represents proportions of a whole.
• Histograms: Displays frequency distribution for continuous data.
• Line graphs: Shows trends over time.
• Scatter plots: Depicts relationships between two variables.