Week 9:Data Analysis, The type of measurement or classification used in data gathering both determines and limits the type of analysis that can be performed. This week, statistical tests that are used to examine differences between groups (as in group research designs) and associations or relationships between variables will be highlighted. You will also consider the difference between statistical significance and clinical significance.
Note: To access this weekâs required library resources, please click on the link to the Course Readings List, found in the Course Materials section of your Syllabus.
Yegidis, B. L., Weinbach, R. W., & Myers, L. L. (2018). Research methods for social workers (8th ed.). New York, NY: Pearson.
- Chapter 13, âAnalyzing Dataâ (pp. 295â297, âThe Data in Perspectiveâ)
Plummer, S.-B., Makris, S., & Brocksen S. M. (Eds.). (2014). Social work case studies: Foundation year. Baltimore, MD: Laureate International Universities Publishing. [Vital Source e-reader].
- Social Work Research: Measuring Group Success
Bauer, S., Lambert, M. J., & Nielsen, S. L. (2004). Clinical significance methods: A comparison of statistical techniques. Journal of Personality Assessment, 82, 60â70.
Retrieved from Walden Library databases.
Gibson, F. H. (2003). Indigent client perceptions of barriers to marriage and family therapy (Dissertation, University of Louisiana at Monroe).
Retrieved from Walden Library databases.
In order to make decisions about the value of any research study for practice, it is important to understand the general processes involved in analyzing research data. By now, you have examined enough research studies to be aware that there are some common ways that data are reported and summarized in research studies.
For example, the sample is often described by numbers of participants and by certain characteristics of those participants that help us determine how representative the sample is of a population. The information about the sample is commonly reported in tables and graphs, making use of frequency distributions, measures of central tendency, and dispersion. Information about the variables (or concepts) of interest when quantified are also reported in similar manner.
Although the actual data analysis takes place after data have been collected, from the initial planning of a research study, the researcher needs to have an awareness of the types of questions that can be answered by particular data analysis techniques.
For this Discussion, review the case study entitled “Social Work Research: Measuring Group Success.” Consider the data analysis described in that case. Recall the information presented in the earlier chapters of your text about formulating research questions to inform a hypotheses or open-ended exploration of an issue.
Post an explanation of the types of descriptive and/or inferential statistics you might use to analyze the data gathered in the case study. Also explain how the statistics you identify can guide you in evaluating the applicability of the study’s findings for your own practice as a social worker. Please use the resources to support your answer.
Respond to a colleague’s post by raising questions about the value of the evidence based on the quantitative or qualitative data analysis described by the classmate. Please use the resources to support your post.
Week 9:Data Analysis
To access your rubric:
Week 9 Discussion 1 Rubric
To participate in this Discussion:
Week 9 Discussion 1
Research studies often compare variables, conditions, times, and/or groups of participants to evaluate relationships between variables or differences between groups or times. For example, if researchers are interested in knowing whether an intervention produces change in the desired direction, they will want to know whether the change is due to chance (statistical significance) or possibly due to the intervention.
In this case, researchers could use a pre and post measurement of the same participants on the condition being treated, or they could compare a group of individuals who receive the intervention to a group that does not receive the intervention. Researchers could also compare two groups of individuals who receive different interventions.
The rigor of the research design helps control for other factors that might account for the changes (e.g., time, conditions, group differences in other factors, etc.). To prepare for this Discussion, consider the concept of statistical significance.
Post your explanation of how the difference between statistical significance and the true importance (clinical significance) of the relationship between variables or the degree of difference between groups affect your practice decision making. Be sure to include an explanation of what statistical significance means. Include an example from a quantitative study that found statistically significant differences. Discuss whether the results of the study wouldâor shouldâinfluence your practice as a social worker. Please use the resources to support your answer.
Respond to a colleague’s post by suggesting how statistical significance can be used in his or her research and practice. Consider practical issues such as whether a social worker is looking for a treatment approach that might be more effective than what he or she has been using, whether the participants in the study are similar or different from the client the social worker is treating, or decisions about whether to continue a program. Please use the resources to support your answer.
Week 9:Data Analysis
To access your rubric:
Week 9 Discussion 2 Rubric
To participate in this Discussion 2:
Week 9 Discussion
This week you analyzed descriptive and inferential statistics and evaluated applicability of case study findings to social work practice. In addition, you analyzed the relationship between statistical significance and practice decision making and evaluated applicability of the study findings for practice as a social worker.
Next week you will be introduced to all that is included in a sound research study.
To go to the next week:
Week 10
Week 9:Data Analysis
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Week 9:Data Analysis
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