Research Articles - Assignment Example

Statistical assignment: Parental attitude perception in children of working and non-working mothers Statistical analysis: Parental attitude perception in children1. The full APA reference of this article is:Gürsoy, F., & Biçakçi, M. Y. (2007). A comparison of parental attitude perceptions in children of working and nonworking mothers. Social Behavior and Personality, 35 (5), 693-706.2. The statistical analysis used in the results section of the article were; independent t-test, one way ANOVA, correlation test and chi square test of independence.3. Examples of statistical analyses in the article.T-test.In the article, a t- test performed showed that the working status of the mother was important () in terms of the scores for perceived loving mother attitudes.

In this example the t-test is performed to compare whether the working and non-working mothers have significant different average values. The mean of the working mothers was 67.22 and the mean of the non-working mothers was 64.34. The variable being measured is the perceived loving attitude of mothers between children of working and non-working mothers. The research question in this t-test analysis was that; is there a significant difference between the mean of the working mothers and the mean of non-working mothers in the perceived loving mother attitude?

One way ANOVAOne way analysis of variance showed that, based on perceived punishing father, there was a significant interaction between mother’s work status and gender [perceived punishing father: ()]. In this case the test is trying to determine, based on perceived punishing father attitude, whether there are significant difference among the means of the four different groups i.e. male children from working mothers, female children from working mothers, male children from non-working mothers and female children from non-working mothers.

Chi-square testIn the article, Chi-square test indicated that the mother’s education was effective in mother’s working status (). In this example, chi-square was used to test whether there was a significant statistical association between the working status of the mother and her education level.Pearson correlation testA correlation test was done between perceived loving mother attitude and perceived loving father attitude. The correlation reports was that there was a positive and highly significant relationship between the two variables (r= 0.472, p=.001).

The research question; is perceived loving mother attitude and perceived loving father attitude correlated4. The alpha level for the article is 0.55. T-testThe degree of freedom () is 278, the value of the test is Using, the critical t-value is 3.09. Since the t-value is less than the critical t-value, this test was not significant.One way ANOVAThe degree of freedom () is 279, the value of the test is The p-value is 0.010. Since this value is lower than the critical p-value, this test was significant hence the null hypothesis must be rejected.

Chi-square testThe degree of freedom () is 2, the value of the test is This value gives a p-value of .000. This p-value is lower than the critical p-value hence the null hypothesis which says that the two variables are independent is rejected. This shows that the test was significant.Pearson correlation testThe degree of freedom is 2, the value of the correlation test r= 0.472.Comparing the value with the critical value of p=0.001, the test was insignificant.6. According to the selected test, the working status of the mother () was insignificant in terms of the score for perceived loving mother attitude.

In the perceived punishing father attitude, the mother’s working status and gender had a significant interaction (). The article proved that the mother’s working status is significantly associated with her level of education (). Finally, the positive correlation (r=0.472) was not significant enough to suggest a relationship between perceived loving mother and perceived loving father attitudes.ReferencesDouglas, C. M. & George, C. R (2011).Applied statistics and probability for engineers. 5th Ed. New York: John Wiley & sons