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Statistics: Anxiety and Sharing Feelings Correlation Report (Assessment)


Correlation Test (First Findings)

Some scholars have held over time that strong correlations between the levels of stress that can lead to depression associated with those experiencing emotional problems or Anxiety exist. Socio-psychological data can be analyzed statistically to establish correlation between two identified variables (Cohen J, Cohen P, West, & Alken, 2003). One variable of significance is the variable GHSEmPer. This variable describes the likelihood that a person may seek help for his or her emotional problems.

The degrees of the given problems are arranged in an ascending order using numbers. 154 subjects were involved in the study out of which there were 38 males and 116 females. The means by genders are summarised in the table below.

Table 1

GHSEmPer Gender Number Mean Standard Deviation
Male 38 35.87 7.55
Female 116 38.85 7.81

On average, approximately 35.87 percent (SD 7.55) of males were found to either seek help for emotional problems or for their depression or anxiety. On the other hand, approximately 38.85 percent (SD 7.81) of the women in the study were found to either seek help for their emotional problems or for their depression or anxiety.

To test whether there was any difference between the mean stress levels by gender. The mean difference between males and females subjects had a statistical significance value of 0.872. Because the value was greater 0.05, the null hypothesis had to be rejected in favour of the alternative hypothesis and we conclude that they are from different gender with respect to the variable GHSEmPer. This situation implies that women are more likely to share their emotional problems or anxiety problems compared to their male counterparts (Zalta & Chambless, 2012), because the mean differences between the two groups are statistically significant.

When testing whether there was a difference in the levels of depression or anxiety affecting individuals by gender, a statistical significant value of 0.079 was found. Because the significant value was greater than 0.05, the null hypothesis was rejected in favour of the alternative hypothesis (Argyrous, 2011). Thus, it was concluded that there was variable difference by gender, as the findings indicate that females are more likely to share their depression or anxiety problems compared to their male counterparts (Zalta et al., 2012). Importantly, the means of the groups are significantly different from each other as the data analysis suggests.

The correlation analysis to determine whether the variables are correlated was performed. Consequently, the correlation value was determined. This correlation value was used to determine the nature and strength of the relationship. The correlation between the two variables is 0.769. This means that 76.9 percent of all the points are correlated to each other directly. So, if a line of best fit is drawn through these values (Rosenthal, 2011) approximately 77 percent of the points will lie on the line directly. The adjusted R square is 0.5913, which means that the variables have a strong positive relationship, and that the probability that a respondent experiences variable GHSEmPer is more likely to experience the second variable (Sharma, 2005); GHSAnx. Therefore, the two variables are highly correlated (Rice, 2007).

Test Analysis (Second Finding)

A study by Zalta et al. (2012) shows that a strong correlation exists between the level of anxiety that can lead to depression and those experiencing emotional problems and the tendency to share their experiences in relation to individual gender. This supposition could be verified by statistical analysis to test whether there is actually any relationship between the two variables with regard to gender (Cohen et al., 2003). The variable of interest in this case is GHSAnx. This variable describes the likelihood that an individual would seek help for his or her emotional problems, while the later describes the likelihood that a person would seek assistance if he or she indicates signs of depression or anxiety.

The degrees of the given problems are arranged in an ascending order using numbers. Like in the former case, 154 subjects were involved in the study of which 38 were males and 116 females. The means by genders are summarised in the following the table.

Table 2

GHSAnx Gender Number Mean Standard Deviation
Male 38 35.45 10.13
Female 116 39.21 8.84

On average, approximately 35.45 percent (SD 10.13) of males were found to seek help for either emotional problems or anxiety. On the other hand, approximately 39.21with (SD 8.89) per cent of the women in the study were found to either seek help informally for emotional problems or depression. This finding corresponds to those of the study conducted by Zalta et al., (2012).

When testing whether there is any difference in the means between the levels of anxiety by gender (Verma, 2013: Wood & Eagly, 2012), a significant value 0.030 with a t- statistic of -2.193 was found. This value being less than 0.05 led the researchers to verify the null hypothesis and reject the alternative hypothesis, and conclude that the variable was from the same population. As both groups’ means were not significantly different from each other, these variables do not depend on the gender of the subject (Lefebvre, 2006).

When testing whether there was any gender difference between the emotional problems that a person experiences and decision to get help in an informal way, a significant value of 0.041 was found and a t statistic of -2.061. The value being less than 0.05, the researchers accepted the null hypothesis and rejected the alternative hypothesis leading them to conclude that the second variable was from the same populations as of the first variable (Dowdy, Wearden, & Chilko, 2004). Because both groups’ means were not significantly different from each other (Lefebvre, 2006) then the variable does not depend on the gender of the subject.

Further, correlation analysis for the tendency to seek assistance and for sharing their experiences was done as explained in the first part of this assignment. The correlation value was determined and used to determine the nature and strength of the relationship. The correlation between the two variables was 0.769. This meant that 76.9 percent of all the points are correlated to each other directly. This meant that if the best line of fit would be drawn through all the possible points (Rosenthal, 2011) approximately 77 per cent of the points will lie on the line directly. This means the variables have a strong positive relationship. A strong positive relationship meant that the probability of a respondent experiencing the first variable to experience the second was high. Therefore, the two variables are positively correlated.

References

Argyrous, G. (2011). Statistics for Research (3rd Edition ed.). Singapore: SAGE Publications Ltd.

Cohen, J., Cohen, p., West, S. G., & Alken, L. S. (2003). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. New Jersey: Lawrence Erlbaum Associates. Inc., Publishers.

Dowdy, S., Wearden, S., & Chilko, D. (2004). Statistics for Research (3rd Edition ed.). New Jersey: Johns Wiley & Sons, Inc.

Lefebvre, M. (2006). Applied Probability and Statistics. Montreal: Springer Science.

Rice, J. A. (2007). Mathematical Statistics and Data Analysis (3rd Edition ed.). Belmont, CA: Duxbury.

Rosenthal, J. A. (2011). Statistics and Data Interpretation for Social Work. London: Lippincott Williams & Wilkins.

Sharma, A. K. (2005). Text Book of Correlations and Regression. New Delhi: Discovery Publishing House.

Verma, J. P. (2013). Data Analysis in Management with SPSS Software. New Delhi: Springer.

Wood, W., & Eagly, A. H. (2012). Biosocial Construction of Sex Differences and Similarities in Behavior. Advances in Experimental Social Psychology, 46, 56-103.

Zalta, A. K., & Chambless, D. L. (2012). Understanding Gender Differences in Anxiety: The Mediating Effects of Instrumentality and Mastery. Psychology of Women Quarterly, 36 (4), 488-499.

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