Need Completed In 12 Hours Must Use Grammarly Zero Plagiaris

Need Completed In 12 Hours Must Use Grammarly Zero Plagiarismpurpose

Need completed in 12 hours. Must use Grammarly. Zero plagiarism Purpose of Assignment The Individual Assignment takes students through multiple studies that research opposing ends of the spectrum: qualitative vs. quantitative, descriptive vs. inferential. It gives students the chance to look at the strengths and weaknesses of each. Each of the designs and methods have different purposes and areas in which they are more suited and students will have this opportunity to see how they fit into different industries and purposes.

Assignment Steps Locate two research studies: one in which the business problem is researched using a qualitative design and the other using a quantitative design. These should be in an industry you are currently working in or are interested in working. Develop a 1,400-word analysis of the research and include the following: Summarize each of the research studies briefly. Discuss the strengths and weaknesses of each design approach. Discuss the strengths and weaknesses of each sampling approach.

Identify the specific situations in which you might choose each of the data collection instruments. Discuss the strengths and weaknesses of statistical analysis use to describe the data. Discuss whether the identified sampling method and data collection approach are appropriate for your own business, industry, or functional area. Cite a minimum of two peer-reviewed sources not including your textbook. Format the assignment consistent with APA guidelines.

Paper For Above instruction

Introduction

Understanding the distinctions between qualitative and quantitative research methods is fundamental for conducting effective investigations within any industry. Each approach offers unique insights and tools, making them suitable for different research contexts. This paper explores two research studies—one employing qualitative methodology and the other quantitative—in the healthcare industry. By analyzing these studies, I will discuss their respective strengths and weaknesses, sampling techniques, data collection methods, and statistical analyses. Additionally, I will evaluate the appropriateness of these methods concerning my own professional context.

Summary of the Qualitative Study

The first research study examined patient experiences with telehealth services in primary care settings. Utilizing a phenomenological qualitative design, the researchers conducted in-depth interviews with twenty patients to gather detailed descriptions of their perceptions, feelings, and attitudes toward remote healthcare delivery. The objective was to explore the nuanced understanding of patient experiences, barriers, and facilitators associated with telehealth.

The study identified themes such as convenience, technological challenges, and perceived quality of care. Data analysis was performed through thematic coding, allowing the researchers to interpret patterns and meanings within the narratives. The qualitative nature enabled rich, contextual insights that are difficult to capture through numerical data.

Summary of the Quantitative Study

The second study investigated the correlation between medication adherence and health outcomes among diabetic patients. Using a descriptive correlational quantitative design, researchers collected numerical data from a sample of 300 patients through structured questionnaires and medical records. The goal was to identify statistical relationships between adherence levels and glycemic control.

Statistical analyses included descriptive statistics, correlation coefficients, and regression modeling to quantify the strength and significance of relationships. The study provided quantifiable evidence supporting the hypothesis that higher medication adherence is associated with better health outcomes. The numerical data allowed for generalization to a larger population under similar circumstances.

Strengths and Weaknesses of Each Design Approach

Qualitative research excels at exploring complex phenomena, capturing context, and understanding meanings behind behaviors. Its strength lies in producing rich, detailed data that reveal insights into individual experiences. However, qualitative studies often face limitations such as smaller sample sizes, which restrict generalizability, and potential researcher bias during interpretation (Creswell, 2014).

Conversely, quantitative research provides measurable, generalizable results through statistical analysis of large samples. Its strengths include objectivity, reliability, and the ability to identify significant patterns or relationships. Nevertheless, quantitative approaches may overlook contextual nuances and the depth of individual experiences, potentially resulting in a superficial understanding of complex issues (Babbie, 2017).

Strengths and Weaknesses of Sampling Approaches

The qualitative study utilized purposive sampling, selecting participants who had experienced telehealth services and could provide rich insights. This approach enhances depth but introduces selection bias and limits the ability to generalize findings (Patton, 2015).

The quantitative study employed random sampling, aiming for representativeness and reducing selection bias. This enhances external validity but assumes the population is homogeneous enough for random sampling to be effective. It may miss subgroups with unique characteristics.

Both sampling methods have their niche: purposive sampling is ideal for exploratory, in-depth studies, while random sampling is suited for studies aiming for generalizability. The choice depends on research objectives—exploratory vs. confirmatory.

Data Collection Instruments and Their Contexts

The qualitative study used semi-structured interviews, suitable for capturing personal experiences and perceptions. This instrument allows flexibility in exploring emerging themes and adapts to participant responses, making it ideal for phenomenological research. However, it requires skilled interviewers and intensive data analysis (Kvale & Brinkmann, 2009).

The quantitative study employed structured questionnaires and medical record reviews, effective for collecting standardized data efficiently and enabling statistical analysis. Such instruments are appropriate when the goal is to measure variables numerically and establish relationships or patterns.

Choosing the appropriate instrument depends on research goals: qualitative tools for depth and context, quantitative tools for measurement and hypothesis testing.

Statistical Analysis: Strengths and Weaknesses

Statistical analysis in the quantitative study—such as correlation and regression—provides a means to quantify relationships, test hypotheses, and infer findings to larger populations. Its strengths include objectivity, precision, and the capacity to handle large datasets efficiently.

However, statistical analysis requires assumptions about data normality and linearity, which, if violated, can compromise validity (Tabachnick & Fidell, 2013). Over-reliance on numbers may ignore context and lead to misinterpretation if not complemented with qualitative insights.

Qualitative analysis, involving thematic coding and narratives, emphasizes understanding meaning and complexity. Its strengths include depth and richness, but it is subject to researcher bias and challenges in ensuring reliability and validity.

Application to My Industry

In my healthcare industry context, combining qualitative and quantitative methods offers comprehensive insights into patient and provider experiences, health outcomes, and service delivery. For example, qualitative interviews can uncover patient perceptions and barriers to adherence, informing targeted interventions, while quantitative data can measure the effectiveness of such interventions across larger populations.

The sampling approach should align with specific project aims: purposive for exploratory phases focusing on in-depth understanding, and random for evaluating broader program outcomes. Data collection instruments like interviews and questionnaires both have roles, depending on whether the focus is on depth or breadth.

Statistical analysis must be carefully selected to suit the data type and research questions, ensuring valid, reliable conclusions that inform policy and practice improvements.

Conclusion

Understanding the distinct advantages and limitations of qualitative and quantitative research methods is critical for designing effective studies within healthcare. By selecting appropriate sampling techniques, data collection instruments, and analytical approaches, researchers can optimize data quality and relevance. Integrating both methods—known as mixed-methods research—can provide comprehensive insights crucial for advancing healthcare quality and patient outcomes. For practitioners and researchers alike, aligning methodological choices with research objectives and context remains paramount for producing meaningful, actionable results.

References

Babbie, E. (2017). Social research methods (12th ed.). Cengage Learning.

Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Sage Publications.

Kvale, S., & Brinkmann, S. (2009). Interviews: Learning the craft of qualitative research interviewing. Sage Publications.

Patton, M. Q. (2015). Qualitative research & evaluation methods: Integrating theory and practice. Sage Publications.

Tabachnick, B. G., & Fidell, L. S. (2013). Using multivariate statistics (6th ed.). Pearson.