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Indian Journal of Pure & Applied Biosciences (IJPAB)
Year : 2020, Volume : 8, Issue : 6
First page : (431) Last page : (435)
Article doi: : http://dx.doi.org/10.18782/2582-2845.8422
Stepwise Regression Analysis of Profile Characteristics of the Respondents towards the Women Empowerment
Sakunthala I. A.*
Department of Basic Engineering & Applied Sciences, Agricultural Engineering College and Research Institute,
Tamil Nadu Agricultural University, Kumulur -621 712, Trichy Dist
*Corresponding Author E-mail: drasextn@gmail.com
Received: 8.10.2020 | Revised: 14.11.2020 | Accepted: 19.11.2020
ABSTRACT
Stepwise regression is an automatic computational procedure that attempts to find the “best” multiple regression model using only statistically significant predictors from a larger set of potential predictive variables. The regression model describes the relationship between a dependent (outcome) variable (Y) and two or more independent (predictor or explanatory) variables (Xj), using a model where Y=B0+B1X1+B2X2+…+ BkXK +eY =B0+B1X1+B2X2+…+ BkXK+e. Computer programs are used to find the Bj weight for each Xj variable so as to minimize the sum of the squared error (e) for cases used to generate the model. The unique contribution of each Xj variable can be tested with a t test and associated p value, using the null hypothesis that Bj = 0 in the population. By using this stepwise regression analysis, the researcher could identify the most influencing independent variables .Thus this study selects 17 variables using judges opinion. Out of 17 independent variables studied, the coefficient of correlation of seven variables were positively significant at 1.00 per cent level of probability. These variables were innovativeness, economic motivation, progressiveness, scientific orientation, self confidence, self responsibility and trainings undergone. Apart from that, the variables such as mother's education, respondent's education, occupation and mental activity had shown significant relationship at 5.00 per cent level of probability. Therefore it could be concluded that the above mentioned 11 variables alone had significant relationship with the extension empowerment. The other six variables had no significant relationship. The study was conducted at Coimbatore District of Tamil Nadu state. The profile characteristics and empowerment were studied from 337 women using well structured Interview schedule.
Keywords: Stepwise regression analysis, Innovativeness, Progressiveness, Economic motivation
Full Text : PDF; Journal doi : http://dx.doi.org/10.18782
Cite this article: Sakunthala, I. A. (2020). Stepwise Regression Analysis of Profile Characteristics of the Respondents towards the Women Empowerment, Ind. J. Pure App. Biosci. 8(6), 431-435. doi: http://dx.doi.org/10.18782/2582-2845.8422
INTRODUCTION
Reforms are needed on several fronts from education and training to land ownership. Women's income have a greater impact on household food security and on improving child health and nutrition. The developmental professionals and the policy makers also divert their attention towards the empowerment of women. But the feminists lacking yardstick to measure their empowerment critically.
It was felt necessary to conduct an empirical research on the involvement of women in the empowerment activities so as to tone up the existing systems of developmental schemes on women's upliftment. Sivarevathi (1996) studied the prime motivating factors responsible for women participation, she found economic (economic necessity and to get programme benefits) and social factors (continue forefather's occupation and for attaining a social status) were the important motivating factors. Gaining additional knowledge was also one of the important motives for the farm women to participate in development programmes. According to Nair and White (1987), extension participation is a process of enabling or empowering rural people to manage their own development. Further, they reported that "people must be able to educate themselves through developing thinking, acting and problem solving abilities. Participation will give individuals a sense of power which will increase their control over the environment and enable them to shape their own destiny", participation in its most developed form is "self management". Ganesan (1989) studied the level of participation in agricultural developmental schemes. The farmer beneficiaries were distributed in low to medium (62.40%) level of participation whereas the farm leaders were distributed in medium to high (80.00%). Hence it was planned to undertake an indepth study on identification of critical variables which were closely associated towards the empowerment of women. With this concept the following objective was planned.
Specific objective
To analyse the relationship between profile variables of women and their empowerment using stepwise regression analysis.
MATERIALS AND METHODS
The research study was undertaken at Coimbatore District of Tamil Nadu state. which was selected based on the no.of women oriented agricultural activities and allied activities. There were about 337 women were involved in this study by employing proportionate random sampling procedure from five blocks. Well structured interview schedule was used to collect the information on profile characteristics and empowerment. In stepwise regression analysis there were two methods viz., step down and step up. In this study, step up method was followed. In this process 17 independent variables were used. Totally seven steps were carried out, whereas the results of the seventh step was as that of sixth step so it was stopped at sixth step. In the step up method of stepwise regression one independent variable was introduced in each step. The variables which were having higher significant value will be included the others will be eliminated.
RESULTS AND DISCUSSION
The stepwise details carried out in the analysis is presented as follows:
Table 1: Step-wise regression analysis of profile characteristics of the respondents towards the women empowerment
|
Variables |
Regression co-efficient |
Std. error |
't' value |
Step I |
|
|
|
|
1. |
Risk orientation |
0.697 |
0.108 |
41.552 |
|
|
R2 = 0.341 |
|
|
Step II |
|
|
|
|
1. |
Risk orientation |
0.505 |
0.120 |
17.650 |
2. |
Self confidence |
0.240 |
0.069 |
11.970 |
|
|
R2 = 0.368 |
|
|
Step III |
|
|
|
|
1. |
Risk orientation |
0.560 |
0.183 |
9.417 |
2. |
Self confidence |
0.346 |
0.128 |
7.699 |
3. |
Innovativeness |
0.222 |
0.l069 |
10.470 |
|
|
R2 = 0.389 |
|
|
Step IV |
|
|
|
|
1. |
Innovativeness |
0.604 |
0.181 |
11.189 |
2. |
Risk orientation |
0.276 |
0.129 |
4.595 |
3. |
Self confidence |
0.213 |
0.068 |
9.845 |
4. |
Trainings undergone |
0.070 |
0.022 |
10.450 |
|
|
R2 = 0.400 |
|
|
Step V |
|
|
|
|
1. |
Age |
0./049 |
0.025 |
3.964 |
2. |
Innovativeness |
0.599 |
0.180 |
11.093 |
3. |
Risk orientation |
0.287 |
0.128 |
5.009 |
4. |
Self confidence |
0.191 |
0.068 |
7.758 |
5. |
Trainings undergone |
0.076 |
0.022 |
12.042 |
|
|
R2 = 0.418 |
|
|
Step VI |
|
|
|
|
1. |
Age |
0.074 |
0.027 |
7.531 |
2. |
Respondents' education |
0.205 |
0.089 |
5.302 |
3. |
Innovativeness |
0.649 |
0.180 |
9.309 |
4. |
Risk orientation |
0.205 |
0.132 |
2.409 |
5. |
Self confidence |
0.159 |
0.069 |
5.219 |
6. |
Trainings undergone |
0.081 |
0.022 |
13.649 |
|
|
R2 = 0.421 |
|
|
Step VII |
|
|
|
|
1. |
Age |
0.074 |
0.027 |
2.744** |
2. |
Respondents' education |
0.205 |
0.089 |
2.303* |
3. |
Innovativeness |
0.649 |
0.480 |
4.051** |
4. |
Risk orientation |
0.205 |
0.132 |
2.992* |
5. |
Self confidence |
0.159 |
0.069 |
2.285* |
6. |
Trainings undergone |
0.081 |
0.022 |
4.694** |
(Women empowerment) = - 0.07956 + 0.074** X1 (Age) + 0.205** X4 (Respondents' education) + 0.649** X9 (Innovativeness) + 0.205** X10 (Risk orientation) + 0.159** X15 (Self confidence) + 0.081** X17 (Trainings undergone)
Step I
In this step risk orientation alone included. The R2 value was 0.341.
Step II
In this step, the dependent variable viz., Self confidence was included additionally. So the R2 value was 0.368. The R2 value was increased by 0.027 units due to the inclusion of self confidence.
Step III
In the step III, the dependent variable 'Innovativeness' was included based on the higher significant value. The R2 value was 0.389. The R2 value increased by 0.021 units due to the inclusion of innovativeness.
Step IV
In this step IV, the dependent variable 'Trainings undergone' was additionally added along with the existing variable. The R2 value was 0.400. Due to the inclusion of the variable trainings undergone there was increase in the R2 value by 0.011 units.
Step V
In this step V, the independent variable 'Age' was included (other variables got less significance than age). The R2 value was 0.418. There was 0.018 unit was increased in the R2 value due to the inclusion of the variable age.
Step VI
In the step VI, the independent variable 'Respondents' education' was included along with the already existing five variables. The R2 value was 0.421. This is due to the inclusion of sixth variable respondents' education. Hence the R2 value was increased by 0.003 units.
Step VII
In the step VII, the R2 value was 0.421 there was no increase in the R2 value. Since the other 11 variables had no higher significant value. So the step up regression analysis was stopped at this stage.
It could be inferred from the Table 1 that there were 11 independent variables have got eliminated from 17 independent variables. The six variables viz., age, respondents' education, innovativeness, risk orientation, self confidence and trainings undergone were derived as most influencing variables towards women empowerment. All these six variables put together have contributed to the tune of 42.10 per cent variation in the changes in overall empowerment. As already indicated, the contribution of all the seventeen variables for the change in overall empowerment was 54.90 per cent. From this it could be implied that the 11 eliminated variables put together were responsible for only 12.80 per cent of variation. Hence their elimination is substantiated.
From the above finding the following inferences could be drawn.
CONCLUSION
Neela (1994) reported that participation in extension activities, by its nature varies in degrees, modes and kinds. The process of participation tends to be unique on every occasion and the kind and degree of participation also tends to differ. Different participative methods were evolved in response to different situations and the product of participation changes from time to time and from location to location. Hence Identifying critical variables which influence more on empowerment would pave way for disseminating right technology or any welfare programmes to right people in right way. Ultimately it would reap the fruitful results.
REFERENCES
Ganesan, R. (1989). Participation Pattern of Officials, Farm Leaders and Farmer Beneficiaries in Agricultural Development Schemes-A Critical Analysis. Unpub. Ph.D., Thesis, TNAU, Coimbatore.
Misra, & Suresh & Singh, C. (1980). Rural Leadership in Haryana: Changing Profile. Kurukshetra, XLVI 7, 42-43.
Neela, M. (1994). Participatory Rural Appraisal: Methodology and Applications. Concept Publishing Company, New Delhi.
Paulmurugan, M. (2002). Prospects of Empowering Farm Womwn in Irrigated Farming System. Unpub. M.Sc. (Ag.) Thesis, TNAU, Coimbatore.
Sivarevathy, A. L. (1996). Participaion of Farm Women in Deveopment Programmes. Unpub. M.Sc. (Ag.) Thesis, TNAU, Coimbatore.
Saravanakumar, M. (2000). Impact of TANWA in the Empowerment of Women. Unpub. M.Sc. (Ag.) Thesis, TNAU, Coimbatore.