Discuss Data Collections and Analysis Methods and Techniques.
Even the most focused research question may contain within it a series of more fundamental and related questions. Once these are determined, the researcher must then determine the kinds of information necessary to answer them. In this assignment, you will identify how you would conduct your study of the best practice model you proposed earlier in the quarter. From there identify a series of evaluation questions which you would propose as an evaluation design. You will also begin to identify the kinds of data you will need, from whom you will gather it, and which methods you will apply to your proposed study.
For your research questions, identify what type of data you will collect in order to address your research question. You will be answering these questions:
Who will your participants be?
Is the data quantitative or qualitative in nature—should it be in the form of numbers or words?
What methods might you apply to glean the information that you seek?
What instruments, measures, or tools would you use in your study?
Also, identify how you would analyze the data that you collect. Will you be conducting statistical analyses of any kind? Or, will you be using coding and categorizing? Will you be using any computer software to assist with the analysis?
Finally, consider the results of the study. Who should know about these results? How will you present them?
By successfully completing this assignment, you will demonstrate your proficiency in the following EPAS and practice behaviors:
C4: Engage In Practice-informed Research and Research-informed Practice
C4.GP.B Apply critical thinking to engage in analysis of quantitative and qualitative research methods and research findings.
Include the following components in your paper:
Restate your overarching research question.
Evaluate critical sub-questions related to a primary research question. In other words, what questions require answers in order to address the primary question?
Propose a relevant pool of participants.
Justify data sources (artifacts, literature, et cetera) relevant to a given research problem. Are you seeking information represented by numbers or words? Stated differently, are you interested in quantitative, qualitative data, or both? Describe these.
Analyze contextually appropriate data-collection tools.
Evaluate the approach to relevant data interpretation. Be sure to explain why you have selected this approach. Consider whether you will use any computer software or programs to assist with the data analysis.
Audience and Medium
Assess the appropriate audience and medium for final data analysis. Include how you propose to present them and what format would be most appropriate to communicate your results to your audience.
VIEW SCORING GUIDE
By successfully completing this assignment, you will demonstrate your proficiency in the following course competencies and scoring guide criteria:
Competency 1: Use practice experience and theory to inform scientific inquiry and research. (C4.GP.A)
Evaluate critical sub-questions related to a primary research question. (C4.GP.B)
Propose a relevant pool of participants. (C4.GP.B)
Justify data sources (artifacts, literature, et cetera) relevant to a given research problem. (C4.GP.B)
Analyze contextually appropriate data-collection tools. (C4.GP.B)
Competency 2: Apply critical thinking to engage in analysis of quantitative and qualitative research methods and research findings. (C4.GP.B)
Evaluate the approach to relevant data interpretation. (C4.GP.B)
Competency 3: Use and translate research evidence to inform and improve practice, policy, and service delivery.(C4.GP.C)
Assess the appropriate audience for final data analysis. (C4.GP.B )
Competency 4: Communicate in a manner that is scholarly, professional, and consistent with expectations for members of the social work profession.
Communicate in a manner that is scholarly, professional, and consistent with expectations for members of the social work profession.
Data Collection Methods:
There are several methods of data collection, including:
Surveys: Surveys are one of the most commonly used data collection methods. They involve asking a group of people a set of questions, which can be conducted through different mediums, such as online, paper, or phone.
Interviews: Interviews involve a researcher asking questions to an individual or a group of individuals to gather information. Interviews can be conducted in-person, over the phone, or online.
Observations: Observations involve watching and recording behavior, actions, or events. Observations can be conducted in a natural setting, such as in a workplace, or in a laboratory setting.
Experiments: Experiments involve manipulating one or more variables to observe the effect on a dependent variable. Experiments can be conducted in a controlled laboratory
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Data Analysis Methods:
After data has been collected, there are several methods of data analysis, including:
Descriptive Statistics: Descriptive statistics involves summarizing the data using measures such as mean, median, mode, range, and standard deviation.
Inferential Statistics: Inferential statistics involves making conclusions about a population based on a sample. This involves hypothesis testing, confidence intervals, and regression analysis.
Content Analysis: Content analysis involves analyzing written or spoken material to identify patterns or themes. This is commonly used in the social sciences to analyze text-based data, such as interviews or surveys.
Data Mining: Data mining involves using software and algorithms to analyze large datasets to identify patterns and relationships. This is commonly used in business and marketing to identify consumer trends.
Data Analysis Techniques:
There are several data analysis techniques that can be used depending on the research question and data type, including:
Qualitative Analysis: Qualitative analysis involves analyzing data that is not numerical, such as text-based data or images. This involves identifying themes or patterns in the data.
Quantitative Analysis: Quantitative analysis involves analyzing numerical data. This involves using statistical techniques to identify patterns or relationships in the data.
Time Series Analysis: Time series analysis involves analyzing data that is collected over time. This involves identifying patterns or trends in the data over time.
Network Analysis: Network analysis involves analyzing the relationships between entities, such as social networks or computer networks. This involves identifying patterns or relationships between entities.
In conclusion, data collection and analysis are important components of research in various fields. The choice of data collection and analysis methods and techniques depends on the research question, data type, and research objectives. Researchers should carefully consider the strengths and limitations of each method and technique when selecting the most appropriate one for their study.