# Multiple regression analysis

## CHAPTER 4 DATA ANALYSIS

### 4.3.1 Multiple regression analysis

H0: The four independent variables (types of industry, health condition, socio-economic status (SES), and source of information are not significantly explaining the variance for level of awareness on health screening benefits provided by SOCSO.

H1: The four independent variables (types of industry, health condition, socio-economic status (SES), and source of information are significantly explaining the variance for level of awareness on health screening benefits provided by SOCSO.

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Table 4.7: Coefficient Unstandardized Coefficients

Standardize d

Coefficients t Sig.

B Std.

Error Beta

(Constant) 7.659 1.060 7.223 .000

Types of Industry .564 .042 .612 13.345 .000

Health Condition -.067 .048 -.068 -1.401 .162

Socio-Economic Status (SES) .139 .040 .161 3.456 .001

Source of Information .289 .083 .158 3.482 .001

Source: Data generated from SPSS version 20.0

There are four independent variables which used to examine the level of awareness on health screening benefits provided by SOCSO. The equation shown as following:

Y= a + β 1X1 + β 2X2 + β 3X3 + β 4X4 + Ɛi

where:

Y= Level of Awareness β = Slope of Coefficient

X1 = Types of Industry X2 = Health Condition

X3 = Socio-Economic Status (SES) X4 = Source of Information

Ɛi = Error term

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By referring to the table 4.7, the regression equation of the level of awareness on health screening benefits provided by SOCSO stated as below:

AWA = 7.659 + 0.564 (TI) - 0.067 (HC) + 0.139 (SS) + 0.289 (SI) where:

AWA = Level of Awareness TI = Types of Industry HC = Health condition SS = Socio-economic Status

SI = Source of Information

Based on the table 4.7, the most significant independent variable is the types of industry since the result shows that t-value is 13.345 and p-value is 0.000, which significantly shows lower than 0.01. Furthermore, it also shows that types of industry are significant to predict the level of awareness on health screening benefits provided by SOCSO. Besides that, contribution of the highest to the variation for the level of awareness on health screening benefits provided by SOCSO is types of industry. This is because the beta value (standardized coefficients) for this predictor variable is the largest which is 0.612 as compare to the others predictor variables (health condition, socio-economic status (SES), and source of information).

Besides, source of information is the independent variable which represent the second most significant in this study with the t-value, 3.482 and p-value, 0.001. The p-value is less than alpha value with 0.01. This shows the source of information is significant to forecast the level of awareness on health screening benefits provided by SOCSO. In addition, the second highest to the variation is source of information due to the beta value (standardized coefficients) of it is the second higher (0.158).

Socio-economic status (SES) is the third significant independent variable.

The t-value is 3.456 and p-value is 0.001. The p-value is less than alpha value with 0.01. This represent that the socio-economic status (SES) is

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significant to predict the level of awareness on health screening benefits provided by SOCSO. Besides, socio-economic status (SES) has the third highest to the variation for level of awareness on health screening benefits provided by SOCSO. It is because the beta value (standardized coefficients) is the third higher with 0.161.

Lastly, the t-value for health condition is -1.401 which represent that there is a negative relationship to the level of awareness on health screening benefits provided by SOCSO. Besides, p-value of health condition is 0.161 which shows greater on the alpha value with 0.10. Therefore, it is not significant in explaining the level of awareness on health screening benefit provided by SOCSO. Health condition contributes the lowest towards the variation of the perceived employability. This is due to the beta value of standardized coefficients for this predictor variable is the smallest which is -0.068 as compared to the others predictor variables.

Table 4.8 Model summary

Model R R Square Adjusted R Square

Std. Error of the Estimate

Change Statistic

R Square Change F Change

1 .705a .497 .490 3.33744 .497 74.282

Source: Data generated from SPSS version 20.0

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Source: Data generated from SPSS version 20.0

a. Predictors: (Constant),Types of Industry, Health Condition, Socio-Economic Status (SES), and Source of Information.

b. Dependent variable: Level of Awareness.

R value defined as the correlation coefficient in between the level of awareness and independent variables which include types of industry, health condition, socio-economic status and source of information. Based on the table 4.8, the R value for four independent variables (types of industry, health condition, socio-economic status (SES), and source of information) with the dependent variable (level of awareness) is 0.705. Hence, it showed that there is high correlation and positive in between the dependent, level of awareness and four independent variables which include types of industry, health condition, socio-economic status and source of information.

Also, the table 4.8 represents the coefficient of determination (R square) that used to explain the variance. The R square figure of the four independent variables is 0.497. This also mean that the independent variables (types of industry, health condition, socio-economic status (SES), and source of information) able to explain 49.7% of the variation in level of awareness.

But, there is also left 50.3% (100% - 49.7%) which are unable to be explained. Therefore, it indicates that there still have another important variables can be explain the level of awareness on health screening benefits provided by SOSCO which are not been considered in this research.

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The table 4.9 showed the p-value is 0.000 which less than the alpha value with 0.01. Also, the F-statistic is 74.282 which showed there is significant.

Hence, the research model is significant in the explanation of the relationship between the dependent and the independent variables. From the result, the independent variables (types of industry, health condition, socio-economic status (SES), and source of information) are significant explain the variance level of awareness. Therefore, null hypothesis (H0) is rejected but still the alternative hypothesis (H1) is accepted.

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