Applications of Statistics in Social Work Research

The main objective of the article is to orient the possibilities of using statistical methods both in education and in research in the areas of Social Work. Social Work and related research, such as Psychiatric Social Work, Medical Social Work, Community Development, Empowerment of rural women, Child rights, Trafficking of Women and Children and others, do require the use of statistical methods & techniques. In professional disciplines like Social Work, students are expected to be able to understand and apply basic statistical concepts, also practice in further projects. Social Workers use statistics for research and analysis of the project’s data in developmental projects, in writing proposals and impact / evaluation studies. Sometimes the research they need to do is a program analysis to determine how effective a Social Work program they have established is. Social Workers do other kinds of social research depending on the issues & problems.

Sociology and Social Work are the study of human society and social interactions. It is a vast field of study and includes a multitude of different fields. In this context, we need to explore the utilization of statistical models and methods in each of these areas. However, as social work profession deals with personal, group and community problems and issues of human attitude & behavior, it is not always possible to quantify and mathematically represent the parameters involved in these studies. Social work study and research involve extensive use of statistical analysis. For example; Regression models are typically used to study the relationships between various social parameters to conclude how or why a social phenomenon occurs. Mathematical models in Social work research used to study social phenomena, which are used to study the attitude and behavior of two individuals, forming the basis for social conventions. It is also used to study the racial separation in the population with the help of Schelling method, which examines the individual choices and behaviors that lead to shared combination.

Learning Statistics within Social Work Education: There are many benefits to a statistics course offered within the discipline. When social work students have a statistics instructor who is also a social worker, they have an opportunity to see a member of their profession who is comfortable, confident, and competent with this material.

Students may also be more likely to view the material as relevant. Unlike a service course, a statistics course offered within professional education would likely use examples from empirical studies that are related to practice. Moran (2005) noted that often statistics courses are taught differently from the core courses within the discipline. As Moran stated that Statistics could be taught in ways that are similar to other professional courses, such as emphasizing how statistics could be used to advocate for clients, analyze social justice issues, or “utilizing (students) own ideas as the medium for analyses throughout the course”. The similarities and overlap in method and content could help students see that statistics are indeed important and relevant to the rest of the curriculum.

In a professional discipline, the most important motivator to learn is a relevant connection to the field. This article describes the attitudes, levels of anxiety and confidence, and ability of students who took an accelerated brief, non-credit bearing statistics course within their Davis & Mirick / Teaching Statistics for social work graduate program compared to students who took a full semester, for credit course.

Feelings and Attitudes towards statistics: In this review, overall, there were no differences in students’ feelings and attitudes towards statistics based on the type of course taken. There was no significant association between feelings or attitudes towards statistics or statistical ability and the type of statistics course nor were there any significant differences in students’ ability to apply statistical concepts. Students who took the accelerated, non-credit statistics course were equally able to use statistics, and no more anxious or less confident because they spent less time in a statistics course. In fact, students in the non credit course were no more likely to support the lack of depth of the course as a barrier to their learning than those who took the full credit course, suggesting that students do not perceive the shorter length of the course as detrimental to their learning.

Practices and experiences of Social Work professionals: The United States, the professional organizations and accrediting bodies emphasize the importance of research to practice, including the use of quantitative methods.

In this context, code of ethics, the National Association of Social Workers (2008) admonishes social workers to “critically examine and keep current with emerging knowledge relevant to social work and fully use evaluation and research in their professional practice”. Students develop the ability to fulfill this ethical imperative through their social work education.

In courses on research and evaluation, they receive training in qualitative and quantitative methods that are used to produce evidence-based findings for enhancing social work practice, policy, and service delivery.

Social workers need to possess statistical knowledge and skills to critically analyze the professional literature, skillfully evaluate their own practice, and best serve their clients. When graduates of social work programs develop an appreciation and understanding of basic statistical concepts, Marson (2007) suggests: “great advances in the knowledge base and the evaluation of social work practice are sure to follow”.

This hopeful perspective is tempered by Knight’s (2015) findings that, despite feeling prepared by social work education to engage in evidence-based practice, many graduates do not employ this practice behavior, avoid literature that describes research, and do not understand the discussion of statistics in research articles.

About Instructor Qualities: Instructor Qualities Instructors can engage students in ways that promote statistics learning. They can bring humor to the topic, which is especially useful in engaging students who hold negative attitudes about statistics. Connections with students outside of the classroom positively affect learning. McGrath (2014) explored the role of instructors’ office hours in student success; students who met with an instructor and engaged in self-assessment improved their performance. As Neumann, Hood stated that the classroom assessment techniques are another tool with which instructors can encourage students to assess their developing competence and offer feedback about the course. This approach provides ongoing communication between the instructor and students, which can serve to strengthen their relationship.

Rationale of the Study

“Statistics is a part of scientific methodology. Each and every aspect of social work applications especially in research statistics is very much essential. It deals with the collection, coding, tabulating, classification, description and interpretation of data obtained by conducting surveys and experiments. Its essential purpose is to describe and draw inferences about numerical properties of populations”.

Statistical methods have highly significant application and practice in social work research. Functions of statistics are numerous: the methods of descriptive statistics have an important application for describing natural phenomena; inferential statistics is used for inductive reasoning about unknown properties of a larger group using the known indicators of the causes; testing of hypothesis most frequently refers to the results of one, two or more causes, on the basis of which it is possible to draw conclusions on the issue /problem of the research, by accepting or refuting an initial hypothesis; regression and correlation analysis, in the most simple case, examines the influence and dependence between two or more variables. If the relationships of a greater number of variables are examined, this is multiple regression and correlation.

Objectives of the Study:

• To ascertain statistical applications in Social Work Research.
• To study the practical usage of statistics methods in social developmental sector.
• To know constrains in finding proper statistical application in Social Work education.

Research Methods and Materials

The study was descriptive in nature hence; researcher has adopted descriptive research design. For this study researcher was used secondary data from journals, books, websites and experiences gained in the profession.

Need & Usage of Statistics in Social Work

For a detailed analysis of a multiple regression model it is necessary to introduce partial correlations and explain the relations between variables using partial correlation coefficient; application of chi-square distribution and chi-square test is important in cases with qualitative variables for which it is known or assumed that are interrelated. Chi-square test is quite a common test based on determining the sum of the quotient of the square of the difference between the observed and expected frequencies and expected frequencies.

As professional social work researchers got an experience in using Chi-square value is having multiple applications, for instance, testing equality of distributions, independence test, contingency coefficient C, and so on; nonparametric tests for independent and dependent samples have also important application in research in social work research. These tests primarily refer to attributive variables. What should also be mentioned is the importance of nonparametric tests in application of the variance analysis method with a single factor, on the basis of ranked data.

Statistic’s methods few applications are useful for deciphering patterns among data points collected from a cohort sample. In other words, when we have collected a bunch of data from a group of people who make up the sample, statistics are used to analyze this data, to group it in various ways that show relationships between the variables the questionnaires were designed to elicit.

Ultimately, the Social Workers try to draw inferences from the patterns revealed. Research hopefully provides us with a more realistic and accurate understanding of the groups of people we work with. It considers the importance that knowledge of data analysis has for social workers and examines the attitudes of educators in the field toward statistics. Statistics help in field of social work determine what areas need more social work intervention, which interventions are the most effective, which interventions are the most cost-efficient.

A statistical analysis must be required to get any project executive to support a new initiative or other upcoming best practice. As with any high demand/ limited resources venture, also we need to focus on the areas and services that will be statistically significant.

Professional social workers use statistics to document social inequality. For example, we use the Coefficient to determine the income distribution of residents of a country, to statistically compare two nations, for example. Also use statistics to determine if there are social differences between two groups of incarcerated people, or if there’s an ethnic pattern in children that are removed from their home.

Social Work Research Context

In social work research, it details both quantitative and qualitative methods and data collection, as well as suggesting the methods appropriate to particular types of studies. It also covers issues such as ethics, social issues, gender and ethnicity, and offers advice on how to write up and present your research.'

Social work research may be defined as “the study of the relationship of professional social workers with their clients, such as the individuals, groups or communities on various levels of interaction or thereby as well as their realistic relationships and functioning within the organizational structure of social agencies. It may be briefly defined as systematic investigation into the problems in the field or social work. From the theoretical point of view, social work research re-examines the special body or knowledge, concepts and theories. But from the utilitarian or practical view point, it tries to evolve a systematize theory and valid concepts, so as to understand the efficacy of different methods / interventions of research work to find out innovative interventions or alternate treatments. Therefore, it can be maintained that social work research is concerned with the problems or issues encountered by social workers. It also includes these composite questions which console the social work practitioners or planners or administrators of social work armed forces whose solution remains in research and which are agreeable to investigation.

Furthermore, one finds hardly any important disparity between the operation of the scientific methods and techniques as used by social work research, in spite of the fact that when some research designs or procedures of research are not suitable to social work research, it would appear to have been necessary to develop the tools and techniques suitable to social work research. Two main statistical methods and techniques are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors, sampling variation).

Since the idea of crunching numbers often is enough to make undergraduate and graduate students cringe, many begin to question why social workers have to take statistics to fulfill their degree requirements. When looking through typical coursework for social workers, statistics is typically the course that social work majors least want to take for a variety of reasons, many of which are rooted in popular misconceptions on the subject. However, the following is a detailed explanation on why having a firm understanding on the apparently unrelated field of statistics is such a very important tool for graduates in order to achieve career success as a social work researcher.

Scope of Statistics in Social Work

Although it is often mistakenly equated with mathematics, statistics is actually more about developing logical reasoning than just number crunching. While it does help to have basic math skills to be successful in statistics, most of the complex calculations in statistics are done with easy-to-use computer software. When conducting social work research with the goal of advancing the knowledge in the field, statistics is an essential tool that enables social workers to draw a story out of the mountains of statistical data unearthed. According to the definition of statistics, it is the science of collecting, analyzing, summarizing, and making inferences from data sets. Since conducting research means you have to make sense of all the data compiled, statistics are enormously important for drawing accurate conclusions about the topic being examined in the research.

Despite the fact that statistics is even more vital for those who wish to devote their career to being a quantitative social work researcher, it is still important for all social workers to have a basic understanding on statistical analysis to be successful. In the majority of Master of Social Work (MSW) degree programs, you will be required to complete a capstone project that can lead to extensive amounts of quantitative or qualitative research. Having a foundational knowledge in statistics will ensure that you have the ability to work with large data sets and make completing your capstone project infinitely easier. Once you begin practicing, possessing statistical knowledge will also help you grasp the latest empirical research findings in social work to stay up-to-date on the most effective intervention techniques as well.

Managing Apprehension in Learners

Since statistics is part of virtually every accredited social work program, it is important for social work students & professionals to be well-prepared for these courses by taking an undergraduate introductory statistics course before entering the program. Not only will having an introductory statistics course on your transcript give you a leg up with the admissions committee, but it will also give you a firm foundation in descriptive statistics, normal distribution, inference testing, and correlation for having a smooth transition to more advanced statistical analyses. Also, make sure that you devote enough time to master the material by taking a statistics course with a lighter course load, so you have the best chances at understanding the time-consuming content.

Social Workers and Social Work researchers use statistics for research, primarily. Sometimes the research they need to do is a program analysis to determine how effective a social program established. Social Workers do other kinds of social research, too. They may want to sample a number of high school teenagers to learn about prevalence of drug use and what kind of drugs are being used. They might want to do research about the effectiveness of a particular mode of therapy and to do this they may ask other Social Workers to complete questionnaires.

Statistics are useful for deciphering patterns among data points collected from a cohort sample. In other words, when you’ve collected a bunch of data from a group of people who make up your sample, statistics are used to analyze this data, to group it in various ways that show relationships between the variables the questionnaires were designed to elicit. Ultimately, Social Workers try to draw inferences from the patterns revealed. Research hopefully provides us with a more realistic and accurate understanding of the groups of people we work with.

Roles of Statistics in Social Work field Practice

As a current student taking statistics in social work, statistics are used by social workers, even if they are not in the process of doing research. Research and statistics inform social workers as to what are the best methods to be used, what populations are the most vulnerable, and a litany of other such questions. These become journal reports that are then scrutinized by peers. These become peer reviewed journal entries. If you are really that interested, do a Google scholar search for peer reviewed articles on any social work topic, from children, to mental health, to substance abuse, to minorities. You will find a glut of information that your local social worker will then try to implement in serving the public.

Social Workers always conduct research to try to learn the truth about social problems, what may be the real underlying causes of social problems, and to evaluate just how effective their interventions to problems are. Typically, Social Workers will use multiple question surveys which they give to a sample of people, or they use data from published tables (demographic, census, or other data). If thirty people are sampled with a ten question survey and each question on the survey is more or less answered the same, what does it mean? Before you can answer that you need to more precisely define “more or less the same. “ Statistics provides the method for doing this. Statistics gives us a number of ways to summarize the data in order to identify any patterns that may exist. Patterns help us to recognize how various social, environmental, or personal characteristics or processes may cause or influence certain social problems or how well certain interventions may elevate them. Statistics help us make sense of research

Challenges and Difficulties Daced in Application of Statistics

• Data Analysis: Data analytics are tremendously important for risk for social work professionals, researchers, students and managers of implementation of social work related projects. They improve decision-making, increase accountability, benefit financial health, and help employees forecast losses and observe performance.
• Quality of information: Mainly, the amount of data being collected, Collecting meaningful and real-time data, Visual representation of data, Data from multiple sources, Inaccessible data, Poor quality data, Pressure from the top, Confusion or anxiety, Scarcity of advanced skills and Scaling data analysis.
• Lack of experts in big data analysis: Apart from these constrains, need for bringing together across disparate data sources, acute scarcity of professionals who understand big data analysis, getting significant insights through the use of big data analytics, getting huge data into the big data platform, and vagueness of data management countryside.
• Difficulties in understanding: Data science is merging of several techniques that include statistics, computer encoding, hacking skills, and a concrete expertise in specific fields, among others. Sometimes social workers needs to in depth learning of advanced new skills in data science and work as professional social work researcher to do effective work.
• Measuring qualitative data: As specialized social workers always facing the issues in analyzing qualitative data due to lack of an appropriate techniques. And facing difficulties in prove the hypothesis in research work as holdup in analyzing data and come to an appropriate conclusion.
• Ethical dilemmas: Data can be a valued asset for organizations Thus, for social work management, data should be seen as a product. Here researchers facing difficulties due to lack of articulation skills and discover the information. Certainly, the increase in the acceptance of communication technologies impacts individuals. Social relations are one of the most significant uses of Internet technologies and tools (Mishna et al., 2012). Fear

Solutions to Overcome from the Difficulties

Depends on the types of research you want to do and the kind of software we can afford. If we want to conduct a pure quantitative research any software would work, but if you want to conduct a mixed research method (combining quantitative and qualitative), we would suggest to take a look at MaxQD. With regard to the affordability, to be careful and choose the software that will cost less and does utility of the packages. Data science approach involves three different domains, including programming, statistics, and a deep understanding of a specific topic. This last element involves specialized expertise, which can range from business to physics, including health care, and social services. Therefore, social work management can take advantage of data possibilities and improve interventions. Presently the specialized social workers use the following advanced software for both quantitative and qualitative data analysis;

The Quantitative Data Analysis Tools

Statistical Package for Social Science (SPSS): SPSS is the most popular quantitative analysis software program used by social scientists. Made and sold by IBM, it is comprehensive, flexible, and can be used with almost any type of data file. However, it’s especially useful for analyzing large-scale survey data. This can be used to produce tabulated reports, charts, and plots of distributions and trends, as well as generate descriptive statistics such as means, medians, modes and frequencies in addition to more complex statistical analyses like regression models. Also this software provides a user interface that makes it easy and intuitive for all levels of users. Easily, perform analyses without having to write command syntax, like in other programs. It is also simple and easy to enter and edit data directly into the program. There are a few drawbacks, however, which might not make it the best program for some researchers. For example, there is a limit on the number of cases you can analyze. It is also difficult to account for weights, strata and group effects with SPSS.

STATA: This software is an interactive data analysis program that runs on a variety of platforms. It can be used for both simple and complex statistical analyses. This tool uses a point-and-click interface as well as command syntax, which makes it easy to use. This is also making it simple to generate graphs and plots of data and results. Analysis in STATA is centered on four windows: the command window, review window, result window and variable window. Analysis commands are entered into the command window and the review window records those commands. The variables window lists the variables that are available in the current data set along with the variable labels, and the results appear in the results window.

The Qualitative Data Analysis Tools

Qualitative Data Analysis Software provides a tool that helps with the qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, and discourse analysis. CAQDAS is Computer assisted qualitative data analysis. Here there are few good qualitative data analysis tools;

• Atlas.ti. ATLAS.ti is one of the used tools for qualitative analysis of large data.
• QDA Miner. QDA Miner is qualitative analysis software that helps you manage documents, and carry out common qualitative analysis tasks.
• Tams Anazyler, Dedoose, NVivo, MAXQDA and Hyper RESEARCH.

Also in recent days, the Aquad, Mendeley and Transana soft ware is also good for social work research to get qualitative analysis based on our collected data and information. Nvivo is good software to use for qualitative data analysis. However you should keep in mind that the software is mostly for organizing and coding data. Therefore, it is always helpful to have a model or theory to provide a framework to your analysis.

Conclusion

The article states the use and importance of statistical methods in social work research. Due to the significance of statistical data analysis it is possible to apply adequate statistical methods, on which the value of acquired results and conclusions is based. We can say that presents the experience of applying statistical method in teaching social work research students. There are also some author’s results, related to applying statistical methods in the field of social work and related research. Lastly the author has focused highlights of using statistics referring to the relations of the most significant demography, socioeconomic, cultural, and ethnic and other aspects.