Biostatistics Module 1: Nature of Statistics

Nature of Statistics

• Biostatistics involves developing and applying statistical methods in biology.
• Significant contributions to statistical advancements in genetics came from various scientists.

Key Figures in Genetics and Statistics

• Gregor Mendel: Pioneered the study of genetic segregation patterns in pea plants using statistics.
• Francis Galton: Established the "Law of Ancestral Heredity."
• William Bateson: Suggested genetic inheritance comes half from each parent.
• Ronald Fisher: Developed essential statistical techniques; authored "Statistical Methods for Research Workers" (1925) and "The Genetical Theory of Natural Selection" (1930).
  • Introduced concepts like ANOVA, p-values, Fisher's exact test, and population dynamics equation.
  • Famous for stating, "Natural selection is a mechanism for generating an exceedingly high degree of improbability."
• Sewall G. Wright: Created F-statistics and defined the inbreeding coefficient.
• J.B.S. Haldane: Authored "The Causes of Evolution," emphasizing natural selection within Mendelian genetics; proposed the primordial soup theory.

Types of Biostatistics

• Descriptive Statistics: Summarizes and describes data.
• Inferential Statistics: Infers population characteristics from sample data.

Components of Descriptive Statistics

• Measures of Frequency: Count, percentage, frequency.
• Measures of Central Tendency: Mean, median, mode.
• Measures of Dispersion: Range, variance, standard deviation.
• Measures of Position: Percentiles, ranks, quartiles.

Methods in Inferential Statistics

• Utilizes random samples to infer population characteristics.
• Two primary methods:
  • Estimation
  • Hypothesis Testing

Variables in Scientific Experiments

• Independent Variables: Controlled or manipulated by the researcher.
• Dependent Variables: Affected by changes to independent variables.
• Control Variables: Held constant to ensure valid results.

Types of Measurement Variables

• Continuous Variables: Measurement precision is dependent on the investigator's equipment.
• Interval Scale Variables: Uniform and meaningful differences, but non-meaningful ratios.
• Ratio Scale Variables: Includes a meaningful zero point (e.g., Kelvin scale).
• Circular Scale: Used for measuring cyclical data such as dates and clock times.

Types of Measurement

• Descriptive: Basic form of measurement.
• Diagnostic: Identifies specific conditions or elements.
• Predictive: Used to forecast outcomes.

Differentiating Variable Types

• Meristic or Discrete Variables: Countable and take on distinct values, typically represented by natural numbers (e.g., number of plants in a quadrant).

Levels of Measurement

• Defined as classifications describing the information conveyed by variable values, with four distinct levels:
  • Nominal: Uses numbers as labels for identification without quantitative significance.