If you find a legitimate PDF or can afford the physical copy, treat it as a reference manual, not a novel. Keep it on your desk, not your shelf. When you face a dataset with strange interactions or non-normal distribution, open Sharma’s chapter on "Data Transformation"—you will likely find the exact solution you need.
| Feature | Jawahar R. Sharma | Falconer & Mackay (Intro to Quant. Genetics) | Singh & Chaudhary (Biometrical Methods) | | :--- | :--- | :--- | :--- | | | Master’s students / Field breeders | Doctoral students / Geneticists | Advanced breeders | | Mathematical Rigor | Moderate, step-by-step | High, assumes calculus | High | | Practical Examples | Excellent (Field crops) | Abstract (Animal/Plant generic) | Good (Focus on Indian crops) | | Emphasis on Path Analysis | Extensive (Best in class) | Minimal | Moderate | | Availability (PDF) | High demand, somewhat restricted | Widely available via NCBI/PubMed | Medium | Modern Relevance in the Genomic Era You might ask: With QTL mapping and Genomic Selection (GS), is Sharma’s statistical book still relevant? If you find a legitimate PDF or can
Don't read linearly. Start with Chapter on Frequency Distributions and Measures of Central Tendency if your stats are rusty. Then jump directly to ANOVA . | Feature | Jawahar R
Take a notepad. Copy the analysis tables (e.g., Diallel table, Path coefficient table) by hand. Sharma’s tables are intuitive. Once you draw them manually, you understand the degrees of freedom and sums of squares intuitively. Don't read linearly