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University of Agricultural Sciences, Bengaluru

University of Agricultural Sciences Bangalore, a premier institution of agricultural education and research in the country, began as a small agricultural research farm in 1899 on 30 acres of land donated by Her Excellency Maharani Kempa Nanjammanni Vani Vilasa Sannidhiyavaru, the Regent of Mysore and appointed Dr. Lehmann, German Scientist to initiate research on soil crop response with a Laboratory in the Directorate of Agriculture. Later under the initiative of the Dewan of Mysore Sir M. Vishweshwaraiah, the Mysore Agriculture Residential School was established in 1913 at Hebbal which offered Licentiate in Agriculture and later offered a diploma programme in agriculture during 1920. The School was upgraded to Agriculture Collegein 1946 which offered four year degree programs in Agriculture. The Government of Mysore headed by Sri. S. Nijalingappa, the then Chief Minister, established the University of Agricultural Sciences on the pattern of Land Grant College system of USA and the University of Agricultural Sciences Act No. 22 was passed in Legislative Assembly in 1963. Dr. Zakir Hussain, the Vice President of India inaugurated the University on 21st August 1964.

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Subject: Agricultural Statistics × Author: DINESH, S INAMADAR × Start date: 2006 ×
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    ThesisItemOpen Access
    STATISTICAL METHODS FOR STUDYING THE EFFECT OF MULTIPLE OUTLIERS IN DESIGNED EXPERIMENTS
    (University of Agricultural Sciences, GKVK, 2013-08-05) DINESH, S INAMADAR; Venugopalan, R
    Design of experiments is the backbone of agricultural research experiments. Adopting RCBD, with an aim to statistically test the significance of several treatments, a given treatment is replicated ‘r’ times to assess its power of repeatability for a trait. However, it so happens that replicated values may not follow a normal pattern but have some outliers/aberrant data, leading to non-significant results in ANOVA. It is also not advised to delete them as the basic principle of randomization will be violated and every observation may carry some useful information for crop scientists to exploit. This calls for employing a robust analysis approach, which gives suitable weights to those outliers based on observed pattern of replications, extracts some information and ensures statistical adequacy. Foregoing thoughts were elucidated by adopting robust ANOVA techniques for comparing various pollination methods (treatments) on seed yield and related traits of Brinjal crop. Cook’s distance measure was computed to identify the outliers in the experimental data. Robust analysis, across eight traits, based on Huber’s and Andrew’s M-estimation methods resulted decreased error mean square as high as 90.03 per cent coupled with 97.17 per cent decrease in Probability of Type 1 error and 85.02 per cent decrease in error mean square coupled with 86.01 per cent decrease in Probability of Type 1 error, respectively. It was observed that by adopting suitable Mestimation procedure, a researcher, without removing an outlier could arrive at required inference about the treatmental differences without violating basic principles of experimental designs.