# Pearson’s Correlation Coefficient

## CHAPTER 4 DATA ANALYSIS

### 4.3.2 Pearson’s Correlation Coefficient

Mukaka (2012) indicated the rules of thumb for coefficient range and strength of association which shown in following:

Table 4.10: Rules of Thumb for Correlation Range Coefficient range Strength of Association

±0.90 to ±1.00 Very high positive (negative) correlation

±0.70 to ±0.89 High positive (negative) correlation

±0.50 to ±0.69 Moderate positive (negative) correlation

±0.30 to ±0.49 Low positive (negative) correlation

±0.00 to ±0.29 Little if any correlation

Source: Adopted from Mukaka, M. (2012). Statistics Corner: A guide to appropriate use of correlation coefficient in medical research. Malawl Medical Journal, 24(3), 69-71.

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Hypothesis 1

H0: There is no significant relationship between types of industry and the level of awareness.

H1: There is a significant relationship between types of industry and the level of awareness.

Table 4.11: Correlation between Level of Awareness and Types of Industry

Level of Awareness Types of Industry

Level of Awareness Pearson correlation .670**

Sig. (2-tailed) .000

Types of Industry Pearson Correlation .670**

Sig. (2-tailed) .000

** Correlation is significant at the 0.01 level (2-tailed).

Source: Data generated from SPSS version 20.0

Direction of relationship

From the table above, there is positive relationship between types of industry and the level of awareness on health screening benefits provided by SOCSO. This is because the value for correlation coefficient is positive.

The types of industry variable have a 0.670 correlation with the level of awareness on health screening benefits provided by SOCSO. This means that when the types of industry are exposure to higher risk, the level of awareness on health screening benefits provided by SOCSO is higher.

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Strength of relationship

The value of this correlation coefficient (0.670) is fall under coefficient range between ±0.50 to ±0.69. Therefore, the relationship between the types of industry and the level of awareness on health screening benefits provided by SOCSO is moderate positive correlation.

Significance of relationship

From the result shown, the p-value is 0.000 less than the alpha value with 0.01. Hence, the null hypothesis (H0) is rejected but accepted the alternative hypothesis (H1). Thus, there is a significant positive relationship between the types of industry and the level of awareness on health screening benefits provided by SOCSO.

Hypothesis 2

H0: There is no significant relationship between health condition and the level of awareness.

H1: There is a significant relationship between health condition and the level of awareness.

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Table 4.12: Correlation between Level of Awareness and Health Condition

Level of Awareness Health Condition

Level of Awareness Pearson Correlation .257**

Sig. (2-tailed) .000

Health Condition

Pearson Correlation .257**

Sig. (2-tailed) .000

** Correlation is significant at the 0.01 level (2-tailed).

Source: Data generated from SPSS version 20.0

Direction of relationship

From the table above, there is positive relationship between health condition and the level of awareness on health screening benefits provided by SOCSO.

This is because the value for correlation coefficient is positive. The health condition variable has a 0.257 correlation with the level of awareness on health screening benefits provided by SOCSO. This means that when the health condition is better, the level of awareness on health screening benefits provided by SOCSO higher.

Strength of relationship

The correlation coefficient value is 0.257 which fall under coefficient range between ±0.00 to ±0.29. Hence, the relationship in between health condition and the level of awareness on health screening benefits provided by SOCSO is little correlation.

Significance of relationship

From the results, it shows that the p-value is 0.000 less than the alpha value with 0.01. Hence, the null hypothesis (H0) is rejected but accepted the alternative hypothesis (H1). Thus, there is a significant positive relationship

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between health condition and the level of awareness on health screening benefits provided by SOCSO.

Hypothesis 3

H0: There is no significant relationship between socio-economic status (SES) and the level of awareness.

H1: There is a significant relationship between socio-economic status (SES) and the level of awareness.

Table 4.13: Correlation between Level of Awareness and Socio-Economic Status (SES)

Level of Awareness Socio-Economic Status Level of Awareness

Pearson Correlation .246**

Sig. (2-tailed) .000

Socio-Economic Status (SES)

Pearson Correlation .246**

Sig. (2-tailed) .000

** Correlation is significant at the 0.01 level (2-tailed).

Note: Data generated from SPSS version 20.0

Direction of relationship

From the table above, there is positive relationship between socio-economic status (SES) and the level of awareness on health screening benefits provided by SOCSO. It is because the correlation coefficient value is showed positive. The socio-economic status (SES) variable has a 0.246 correlation with the level of awareness on health screening benefits provided by SOCSO. This means that when socio-economic status (SES) is higher, the level of awareness on health screening benefits provided by SOCSO is higher.

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Strength of relationship

The correlation coefficient value is 0.246 which fall under coefficient range between ±0.00 to ±0.29. Hence, the relationship in between socio-economic status (SES) and the level of awareness on health screening benefits provided by SOCSO is little correlation.

Significance of relationship

According to the result, the p-value is 0.000 less than the alpha value with 0.01. Hence, the null hypothesis (H0) is rejected but accepted the alternative hypothesis (H1). Thus, there is a significant positive relationship in between socio-economic status (SES) and the level of awareness on health screening benefits provided by SOCSO.

Hypothesis 4

H0: There is no significant relationship between source of information and the level of awareness.

H1: There is a significant relationship between source of information and the level of awareness.

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Table 4.14: Correlation between Level of Awareness and Source of Information

Level of Awareness Source of Information

Level of Awareness Pearson Correlation .408**

Sig. (2-tailed) .000

Source of Information Pearson Correlation .408**

Sig. (2-tailed) .000

** Correlation is significant at the 0.01 level (2-tailed).

Source: Data generated from SPSS version 20.0

Direction of relationship

From the table above, there is positive relationship between source of information and the level of awareness on health screening benefits provided by SOCSO. This is because the value for correlation coefficient is positive. The source of information variable has a 0.408 correlation with the level of awareness on health screening benefits provided by SOCSO. This means that when the source of information is higher, the level of awareness on health screening benefits provided by SOCSO is higher.

Strength of relationship

The value of this correlation coefficient (0.408) is fall under coefficient range between ±0.30 to ±0.49. Therefore, the relationship between the source of information and the level of awareness on health screening benefits provided by SOCSO is low positive correlation.

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Significance of relationship

As shown in the result, the p-value is 0.000 less than the alpha value with 0.01. Hence, the null hypothesis (H0) is rejected but accepted the alternative hypothesis (H1). Thus, there is a significant positive relationship in between source of information and the level of awareness on health screening benefits provided by SOCSO.

### 4.4 Conclusion

In summary, the sample data obtained from the questionnaire survey’s result was been summarized and interpreted by using SPPS. However, the analysis of this study was allocated into various elements which are descriptive analysis, scale measurement, and inferential analysis. Furthermore, tests had been conducted are the Pilot Test, Reliability Test, Multi Regression Analysis, Model Summary, ANOVA, and Pearson’s Correlation Coefficient. The analysis results and interpretation will be used in the next chapter for the purpose of discussions, conclusions, and implications of the overall research.

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### CHAPTER 5: DISCUSSION, CONCLUSION AND

Outline

DOKUMEN BERKAITAN