Biostatistics for Biological Data Analysis

Biological Data & Statistical Principles Revision Sheet

1. 📌 Essentials

• Statistics: Science of analyzing numerical data to infer biological phenomena.
• Biostatistics: Application of statistical methods to biological and medical data.
• Population: Entire set of units; Sample: Subset used for inference.
• Variables: Qualitative (nominal, ordinal); Quantitative (discrete, continuous).
• Data Organization: Data matrices, classification, frequency distributions.
• Descriptive Stats: Mean, median, mode (central tendency); variance, SD, IQR (dispersion).
• Probability: Likelihood of an event; values between 0 and 1.
• Normal Distribution: Symmetric bell curve; 68-95-99.7 rule.
• Correlation (r): Measures linear association; ranges from -1 to +1.
• Regression: Predicts one variable from another; Y = a + bX.
• Hypothesis Testing: Null vs. alternative; p-value indicates significance.
• Outliers & Skewness: Outliers are points outside 1.5×IQR; skewness indicates asymmetry.
• Causality: Requires cause-effect relationship, not just correlation.

2. 🧩 Key Structures & Components