Data Analysis
Descriptive statistics
Descriptive statistics were conducted on a dataset composed of 20 test score results on prejudice measured on a scale from 1 to 100. The mean score was 84.7, the median score was 87, and the mode was 87.
Independent T-Test
An independent t-test compared the memory test score means between a group that received treatment (N= 34, Mean= 5.06, Standard deviation= 3.402) and a group that received no treatment (N= 38, Mean= 6.03, Standard deviation= 2.112). The significance value is 0.147. This value is much higher than the standard value of 0.05, showing no statistically significant difference between the results. The degree of freedom of this t-test is 70. From this value, the critical value is 1.995. The obtained value from the dataset is -1.466. Since the critical value is larger than the obtained value, we accept the null hypothesis and assert that the difference between the treatment and no treatment group occurred by chance.
Pearson’s correlation
The relationship between the level of education measured in years and the annual income of twenty individuals was analyzed using Pearson’s correlation. There is a statistically significant positive correlation between the number of years an individual has studied and their annual income. The yearly income increases with the increase in the number of years one studied. The p-value is 0.01, below the standard p-value cut off of 0.05, showing that this relationship did not occur by chance. The correlation coefficient (r) is 0.574, indicating a moderate relationship between the variables (Salkind & Frey, 2020). The correlation of determination (r2) is 33% variance, showing that 33% of the variation in the level of education is accounted for by the annual income, further strengthening the relationship between the two variables. In conclusion, the results indicate a moderate, statistically significant relationship between the level of education and the individuals’ annual income.
Discussion
Descriptive statistics are used to get a rough overview of the data (Salkind & Frey, 2020). In the first dataset, the mean, median, and mode of the prejudice scores were obtained using SPSS. The mean shows the average score in the dataset; the mode offers the most common score in the dataset, and the median is the point where 50% of the recorded scores fall either above or below it (Salkind & Frey, 2020). The results also showed that there were no missing values and were ready for further analysis.
An independent T-Test is used to compare the differences in mean and standard deviation between two groups that are not related to each other (Salkind & Frey, 2020). It is an essential tool in hypothesis testing. The comparison was between the group that received treatment and the group that received no treatment in the dataset. The results show no statistically significant difference between the two groups, and the differences in the test scores between the two groups occurred by chance. This means that there is no difference in the memory capabilities between the group that received the treatment and the group that did not.
Lastly, a Pearson’s correlation was used to compare the relationship between the education levels of 20 participants and their annual income. The Pearson’s correlation is used to determine the relationship between two variables (Salkind & Frey, 2020). The results from the dataset indicated a moderate, statistically significant positive relationship between the number of years an individual studied and their annual income. An increase in the number of years one studied correlated to the individual’s yearly income rise.
Research to Social Work Practice
Research is crucial to social work practice. Research helps to uncover social problems and societal trends (Monette, Sullivan, DeJong, & Hilton, 2014). For example, research can be used to compare the relationship between the economic state and the rate of juvenile delinquency. Such studies can help inform social workers on the best social policies to implement to prevent youth from falling into delinquency. The research can also inform the social workers on the most problematic neighborhoods in the community which are in dire need of social programs and allows the social workers to focus their attention on these locations (Monette, Sullivan, DeJong, & Hilton, 2014).
Research can also monitor the impact of the existing social programs in the community (Monette, Sullivan, DeJong, & Hilton, 2014). A study can determine the effect of a social program by comparing the differences between those who partake in the social program and those who don’t participate. The social worker can use these results to determine the areas they need to improve in the social program and the program’s applicability in other communities (Monette, Sullivan, DeJong, & Hilton, 2014). Therefore, research can be used as a quality control tool to ensure that social programs positively impact society.
Social workers can use research to improve their practice. Social workers can employ evidence-based strategies in their practice by reading social work studies and identifying strategies that would be effective in their community. They can also use research to evaluate the impact of their work on the community by conducting a study to determine the rate of improvement of their patients (Monette, Sullivan, DeJong, & Hilton, 2014). Doing so improves the quality of service of the social worker and ultimately serves to benefit the community. From the above examples, it is clear that research is crucial to social work practice.
