Introduction

This course is designed to understand the statistical procedures and techniques to the agricultural researcher which they need to know in order to design, implement, analyze, and interpret the results of most experiments with crops. Designed specifically for the non-statistician, this valuable guide focuses on the practical problems of the field researcher. Throughout, it emphasizes the use of statistics as a tool of research—one that will help pinpoint research problems and select remedial measures.

Objective

Statistical education for agriculturists tries to give them a solid foundation in statistics. An emphasis is placed on mastering a wide use of statistical methods in order to allow the students to apply these techniques in many fields of agricultural science like: field crops production, vegetable crop production, horticulture, fruit growing, grape production, plant protection, livestock, veterinary medicine, agricultural mechanization, water resources, agricultural economics etc. Problems and dilemmas encountered in statistical education will be presented and some ideas on how to improve the teaching of agricultural statistics. It is expected that the statistical knowledge achieved by finished agricultural students will provide a solid foundation for master degree studies in Biometrics.

Course Contents

• Basic priciples of experimental design
• Layout analysis of Completely Randomized Design
• Randomized Complete Block Design (Estimation of missing observations also)
• Latin Square Design (Estimation of missing observations also)
• Split Plot Design and its variations
• Multiple comparison tests
• Effects of violation of assumptions of underlying ANOVA
• Simple and Multiple Regression
• Logistic Regression and Odd Ratios
• Survival Analysis
• Dose Response Curve
• Simple Correlations
• Multiple Correlations
• Partial Correlations
• Analysis of count and frequency data
• Contigency Table
• Diversity Indices

Recommended Books:

1. Mead, R. (1990). The design of experiments: statistical principles for practical applications. Cambridge university press.

2. d Steel, R. G., & Torrie, J. H. (1986). Principles and procedures of statistics: a biometrical approach. McGraw-Hil

3. Box, G. E., Hunter, W. H., & Hunter, S. (1978). Statistics for experimenters (Vol. 664). New York: John Wiley and sons.

4. Tabachnick, B. G., Fidell, L. S., & Ullman, J. B. (2007). Using multivariate statistics (Vol. 5, pp. 481-498). Boston, MA: Pearson

5. Dillon, W. R., & Goldstein, M. (1984). Multivariate analysismethods and applications (No. 519.535 D5).

Time Table

Monday 12.40 PM - 1.30 PM

Tuesday 9.40 AM - 10.30 AM

Thursday 12.10 PM - 1.00 PM

Distribution of Marks:
Mid Exam:           30

Final exam:          50
Sessional (Assignment,Presentation,Participation,Attendance,Quizes)    20