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The Journal of Research ANGRAU

Contents of 41(1) 2013 - acharya ng ranga agricultural university

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ABIRAMI et al<br />

socio-economic impact. This might be due to the fact<br />

that higher risk oriented farmers adopt the innovations<br />

and get more yield and higher income. Hence, such<br />

type <strong>of</strong> relation existed in the study. This finding was<br />

in line with the findings <strong>of</strong> Chandrasekhar et al. (2005)<br />

and Manoj(2008).<br />

c) Multiple Linear Regression <strong>of</strong> selected<br />

independent variables with socio-economic<br />

impact.<br />

An attempt was made to find out the amount <strong>of</strong><br />

contribution made by the independent variables in<br />

explaining the variation in the dependent variable<br />

through multiple linear regression. <strong>The</strong> results are<br />

presented in Table 3.<br />

Table 3. Multiple regression analysis <strong>of</strong> Pr<strong>of</strong>ile <strong>of</strong> beneficiary farmers and the socio-economic impact<br />

S. No Variables<br />

Regression<br />

coefficient (B)<br />

Standard error<br />

‘t’ value<br />

1. Age<br />

-6.3303 0.7039 -8.9927**<br />

2. Education<br />

0.7092 0.3255 2.1784NS<br />

3. Land Holding<br />

0.4241 0.4370 0.9704NS<br />

4. Farming Experience<br />

4.6575 0.6232 7.4733**<br />

5. Information sources utilization -0.4021 0.0695 -5.7790**<br />

6. Training Received<br />

3.3325 0.5538 6.0164**<br />

7. Economic Motivation<br />

1.4766 0.2322 6.3584**<br />

8. Scientific Orientation<br />

0.3394 0.1763 1.9248NS<br />

9. Innovativeness<br />

0.7704 0.1235 6.2369**<br />

10. Risk Orientation<br />

1.7744 0.2070 8.5691**<br />

R 2 = 0.861; NS = Non Significant;<br />

** Significant at 0.01 level <strong>of</strong> probability<br />

<strong>The</strong> Ten independent variables with the<br />

socio-economic impact <strong>of</strong> the project taken on<br />

Multiple Linear Regression Analysis gave the R 2 (Coefficient<br />

<strong>of</strong> multiple determination) value <strong>of</strong> 0.861. It<br />

indicates that all the selected independent variables<br />

put together contributed 86.10 per cent <strong>of</strong> the total<br />

variation in the socio-economic impact <strong>of</strong> the project<br />

by the beneficiary farmers, leaving the rest to<br />

extraneous factors. <strong>The</strong> independent variables viz.,<br />

farming experience, training received, economic<br />

motivation, innovativeness and risk orientation<br />

contributed significantly to the socio-economic impact<br />

<strong>of</strong> the project. <strong>The</strong> variable scientific orientation was<br />

not having significant value, but the value is near to<br />

significant t –value (1.980272). So, it also could be<br />

considered as significant<br />

REFERENCES<br />

Baswarajaiah, V.2001. Impact <strong>of</strong> Edira Watershed<br />

Development Programme on farm families in<br />

Mahaboobnagar District <strong>of</strong> Andhra Pradesh.<br />

M. Sc. (Ag.) <strong>The</strong>sis submitted to Acharya N<br />

G Ranga Agricultural University, Hyderabad,<br />

India.<br />

91

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