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Data Collection and Analysis

Our data analysis process is collaborative, flexible, and tailored to your project's specific needs. We support both qualitative and quantitative data analysis, offering methodological rigor and best practice alongside clear communication. All analyses are guided by data governance, transparency, and reproducibility principles to ensure that results are both statistically sound and policy-relevant.​

General Procedure

Before Analysis

  • We begin by collaborating with you to clarify the objectives, scope, and intended outcomes of the analysis.

  • We may request access to relevant datasets, completed surveys, codebooks, or supporting documentation.

  • Based on your input and the data available, we create or refine a data analysis plan to ensure alignment with your goals in mind.

Data Cleaning and Preparation

  • Upon request, we clean and preprocess the data to ensure accuracy, completeness, and consistency—addressing missing data, low responses, outliers, or formatting issues.
     

Preliminary Analysis

  • We perform summary statistics or exploratory analyses to better understand the data's structure and quality, setting the stage for more in-depth analysis.
     

Primary Analysis

  • We conduct in-depth analysis to identify key patterns, trends, relationships between variables, or to test hypotheses, address objectives, or answer research questions, as appropriate to the defined goals

Data Visualization

  • Throughout the analysis, we use visual tools—such as charts, graphs, or dashboards—to communicate findings clearly and tell a compelling data story.
     

Reporting and Feedback

  • We present initial findings and interpretations for your review, with clear summaries and visualizations.

  • Your feedback is encouraged—we’re happy to discuss insights, clarify results, or refine the analysis based on evolving questions.
     

Finalization

  • Incorporating your input, we finalize the analysis and deliver a comprehensive report detailing the methods, results, and interpretation.

Methods Information

Quantitative methods may include the following methods, as appropriate:

  • Power and sample size analysis

  • Data dictionary development or verification

  • Descriptive statistics

  • Trend visualization, correlation analysis, and/or factor analysis (to examine relationships within the data)

  • Regression analysis, t-test, ANOVA, chi-square, and/or nonparametric counterparts as appropriate (to compare groups, conditions, or predictive analytics)

  • Psychometric assessments
     

Qualitative methods may include:

  •   Transcript development and/or quality verification

  • Development of a codebook

  • Memoing and reflexive journaling

  •  Systematic coding of recurring concepts, patterns, sentiments, or narratives

  • Thematic, content, framework analysis,  Rapid Assessment Procedures (RAPID) or Rapid Qualitative Inquiry (RQI) (for time-sensitive or iterative evaluations)

  •  Triangulation across data sources or methods

  • Integration of qualitative findings with quantitative data (mixed-methods synthesis) (when applicable)

Call 

Email 

(561) 603-2350

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