Insights

Practical Thinking on Data, Statistics, Research & Analytics

Welcome to Insights, where I share practical knowledge, analytical perspectives, tutorials and lessons drawn from working with real-world data, research problems and analytical tools. The goal is to make data and statistics easier to understand and, more importantly, easier to apply to real research, business and decision-making problems.

Data Analytics Statistics Research Stata Business Intelligence Machine Learning Real-World Data

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Data Analytics

Practical articles on turning raw data into useful information, from data exploration and cleaning to analysis, visualization and interpretation.

Topics include:

Data Cleaning Exploratory Data Analysis Missing Data Data Transformation Data Quality Analytical Workflows Visualization Reporting
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Statistics

Understanding statistical methods beyond commands and software. I break down statistical concepts with an emphasis on when to use them, why they are appropriate and how to interpret the results.

Topics include:

Descriptive Statistics Hypothesis Testing T-tests Chi-square ANOVA Correlation Regression Logistic Regression Survival Analysis Panel Data Time Series
Explore Statistics

Research & Methodology

Practical guidance for moving from a research idea to a structured analytical study.

Topics include:

Research Questions Study Design Variable Selection Data Sources Statistical Analysis Plans Quantitative Research Secondary Data Analysis Interpretation Reporting
Explore Research

Business Intelligence & Visualization

From Numbers to Decision-Support Information

Insights on transforming operational and business data into information that managers and decision-makers can understand and use.

Topics include:

Power BI Dashboards KPI Development Data Modelling Business Reporting Sales Analytics Financial Analytics Executive Reporting Data Storytelling
Explore Business Intelligence

Machine Learning & Predictive Analytics

Moving From Historical Data to Prediction

Practical insights into using statistical and machine-learning methods for prediction, forecasting and segmentation.

Topics include:

Machine Learning Predictive Modelling Customer Analytics Customer Lifetime Value Customer Segmentation RFM Analysis Clustering XGBoost Forecasting Model Evaluation
This section can also build on my published research on machine-learning-based Customer Lifetime Value prediction in retail.
Explore Machine Learning
Stata Insights

From Stata Commands to Complete Analytical Workflows

This section focuses on using Stata for real-world research and data analysis. Rather than presenting isolated commands, the content demonstrates how Stata fits into the complete analytical process.

Topics include:

Importing Data Do-Files & Reproducible Analysis Data Cleaning Managing Missing Data Merging & Appending Datasets Creating & Recoding Variables Descriptive Statistics Statistical Tests Regression Analysis Survey Analysis Panel Data Analysis Data Visualization Exporting & Reporting Results
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Real-World Database Insights

Learn Through Real Data

A major focus of my work is demonstrating how analytical methods are applied to real-world databases rather than relying only on simplified example datasets. Insights cover working with data sources such as:

NHANES

National Health and Nutrition Examination Survey

Topics can include dataset selection, XPT files, merging components, survey weights, variable construction and statistical analysis.

NAMCS & NHAMCS

National Ambulatory Medical Care Survey & National Hospital Ambulatory Medical Care Survey

Practical analysis of healthcare utilization, patient characteristics and ambulatory/emergency care data.

SEER

Surveillance, Epidemiology, and End Results

Cancer incidence, patient characteristics, outcomes and survival analysis.

MIMIC-IV

Clinical and critical-care data analysis.

TCGA

Cancer genomic and clinical data analysis.

CDC WONDER

Population, mortality and public-health data.

DHS

Population, demographic and health survey analysis.

CCHS

Canadian Community Health Survey data and population-health analysis.

World Bank Indicators

Economic, development, financial and population indicator analysis, including cross-country, time-series and panel-data applications.

Explore Real-World Data
Watch & Learn

Wilfred The Analyst on YouTube

Prefer practical demonstrations?

My YouTube content focuses on solving real-world research problems using Stata, from study conceptualization and research design through data management, statistical analysis, interpretation and reporting.

Tutorials use datasets including NHANES, NAMCS, NHAMCS, SEER, MIMIC-IV, DHS and other real-world data sources.

Visit Wilfred The Analyst on YouTube

Insights Categories

For the website filtering and navigation, use the categories below.

All Insights Stata Statistics Research Real-World Data Data Analytics Business Intelligence Machine Learning Data Visualization

Each article card should display: Category Article Title Short Description Publication Date Reading Time Read Article

Learn. Apply. Keep Growing.

New insights will cover practical problems encountered when working with real data, statistical analysis, research and analytical technologies.

Follow my work for new tutorials, articles, datasets and analytical resources.

Need More Than an Article?

Let's Work on Your Data.

If you're dealing with a dataset, research question or analytical problem that requires professional support, you can engage me directly.

Hire Me Request a Consultation