An Overview of Statistical Techniques for Analysis of Data in Agricultural Research | Chapter 11 | Emerging Issues in Agricultural Sciences Vol. 8

 The significance of statistical analysis is paramount in research, particularly in situations involving the collection, classification, analysis, and interpretation of numerical data. Statistical principles find widespread application in various types of experimental studies and serve as a critical component in agricultural research endeavors. The inherent variability present in commonly used experimental materials within agricultural research necessitates the utilization of statistical methods, leading to numerous advancements and innovations in the field of statistics. The selection of an appropriate tool for data analysis and subsequent processes involving statistical components has become a matter of concern. This chapter delves into the diverse statistical techniques essential for the analysis of agricultural data and the derivation of valid conclusions.

Author(s) Details:

Rahul Banerjee,
ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi, India.

Bharti,
ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi, India.

Pankaj Das,
ICAR-Indian Agricultural Statistics Research Institute, Library Avenue, Pusa, New Delhi, India.

Varun Srivastava,
Department of Computer Science and Information Technology, Jaypee Institute of Information Technology, Noida, India.

Ankita,
Department of Agricultural Statistic and Computer Application, Birsa Agricultural University, Kanke, Ranchi, India.

Suraj Kataria,
Department of Anthropology, University of Delhi, Delhi, India.

Bulbul Ahmed,
Department of Agriculture, Galgotias University, Greater Noida, India.

Nitin Varshney,
Department of Agricultural Statistics, Navsari Agricultural University, Navsari, India.

Please see the link here: https://stm.bookpi.org/EIAS-V8/article/view/12877