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Hello R Markdown

R Markdown This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com. You can embed an R code chunk like this: summary(cars) ## speed dist ## Min. : 4.0 Min. : 2.00 ## 1st Qu.:12.0 1st Qu.: 26.00 ## Median :15.0 Median : 36.00 ## Mean :15.4 Mean : 42.98 ## 3rd Qu.:19.0 3rd Qu.: 56.00 ## Max. :25.0 Max. :120.00 fit <- lm(dist ~ speed, data = cars) fit ## ## Call: ## lm(formula = dist ~ speed, data = cars) ## ## Coefficients: ## (Intercept) speed ## -17.579 3.932 Including Plots You can also embed plots. See Figure 1 for example:

Tuesday, December 1, 2020 Read
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Data Science

1. What is Data Science & Machine Learning? Data Science and Machine Learning (ML) provide powerful tools for finding patterns, making predictions, and generating insights from complex and high-dimensional datasets. In academic and applied settings, these techniques are essential for uncovering structure in messy data, exploring heterogeneity, and automating decision-making processes. Whether you’re working with clinical data, behavioral tracking, or large-scale surveys, I bring a research-grounded perspective to building and interpreting ML models that are robust, interpretable, and suited to your unique questions.

Monday, June 8, 2020 Read
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Data Visualization & Dashboards

1. What is Data Visualization? Data visualization transforms raw numbers into meaningful, visual narratives. Whether you’re exploring a dataset, presenting results to stakeholders, or building an interactive dashboard for decision-making, the right visual can make your data clear, compelling, and actionable. In research, health, and applied science contexts, strong visualizations bridge the gap between complex methods and real-world understanding. I design plots, dashboards, and reporting tools that are not only technically correct — but intuitive, polished, and publication-ready.

Monday, June 8, 2020 Read
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Statistical Modeling

1. What is Statistical Modeling? Statistical modeling is the foundation for turning complex questions into meaningful, data-driven answers. Whether you’re analyzing longitudinal data, running an experiment, or exploring latent constructs, the right model helps you uncover patterns, quantify uncertainty, and test theoretical frameworks. With years of experience in academic and applied research, I offer modeling support that balances methodological rigor with practical impact — always tailored to your data, research questions, and audience.

Monday, June 8, 2020 Read
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Statistical Programming & Package Development

1. What is Statistical Programming? Statistical programming bridges the gap between data analysis and automation. Whether you’re analyzing complex datasets, simulating models, or building reusable workflows, clean and efficient code ensures that your results are reproducible, transparent, and scalable. In academic and applied research, statistical programming isn’t just a technical detail — it’s a foundation for good science and streamlined collaboration. I help researchers and teams turn ideas into tools, pipelines, and packages that deliver lasting value.

Monday, June 8, 2020 Read
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Study Planning

1. What is Study Planning? Effective research starts with a solid plan. Study Planning & Design is about crafting research proposals, study protocols, or analysis plans that are methodologically sound and geared for success. Whether you’re preparing a grant proposal, designing a clinical trial, or planning a behavioral study, robust planning is the foundation for reliable, reproducible results. 2. What I Offer I work with researchers and organizations to structure studies that are both innovative and scientifically rigorous. My service bridges the gap between methodological theory and practical execution.

Monday, June 8, 2020 Read
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Workshops & Training

1. What are Workshops & Training Sessions? Workshops and training sessions are interactive, hands-on experiences designed to upskill teams and individuals in statistical methods, data science, and research design. Whether you need a one-time session or a series of training workshops, these sessions can transform how you approach data, model selection, and reproducible research. In both academic and industry settings, effective training bridges the gap between theoretical knowledge and practical application. My workshops are built to empower your team to harness state-of-the-art statistical techniques and tools in R and Python.

Monday, June 8, 2020 Read