Agron Info Tech

Clustering starts with one thing: distance.

If you do not understand how distance works, then cluster analysis will always feel confusing.

In this video, I explain the foundation of clustering in R using a real dataset. You will learn how distance is calculated between observations, how a distance matrix is built, why scaling matters, and how categorical variables can be handled using dummy variables and binary distance.

This video is especially useful for students, researchers, and anyone learning cluster analysis, machine learning, data science, or unsupervised learning in R.

Watch the full video and build the most important concept behind clustering the right way.

, , , , , , ,

Most regression tutorials ignore one major problem: survey design.

If your data comes from a complex survey like NHANES, then a normal regression can give misleading results.

In this video, I show how to run survey-weighted regression in R using svyglm, compare it with a naive regression, and interpret the results properly.

In this lesson, you’ll learn how to:
build a survey design,
fit a survey-weighted regression model,
compare weighted vs unweighted modeling results,
interpret coefficients correctly,
and visualize predicted BMI trends across age.

This is especially useful for students, researchers, public health analysts, epidemiologists, and anyone working with real survey data in R.

Watch the full video and learn how to model survey data the right way.

, , , , , , ,

Most people compute means on survey data the wrong way.

If your dataset has weights, strata, and PSU variables, then a simple average may not represent the real population.

In this video, I use NHANES in R to show how to correctly analyze quantitative survey data using:

1. weighted means,
2. confidence intervals,
3. weighted quantiles,
4. weighted histograms,
5. and group comparisons by gender.

This is essential for anyone working with public health data, survey research, epidemiology, biostatistics, or official datasets.

Watch the full video and learn how to make your numeric summaries actually reflect the population.

, , , , , , ,

Most people analyze survey categories the WRONG way.

If your dataset has weights, strata, and PSUs, then simple percentages can mislead you.

In this video, I use NHANES and show how to correctly analyze categorical variables in R using survey-weighted tables and population-correct proportions.

You’ll learn how to:
Survey-weighted frequency tables, population proportions, conditional proportions, and a segmented bar chart that makes patterns obvious.

If you work with health surveys, social surveys, research data, or public datasets, this is essential.

, , , , , , ,

STOP Ignoring Survey Weights in Your Data Analysis!

If you've ever seen a column called weight in a dataset and thought:

“Can I just ignore this?”

This video will change how you analyze survey data forever.

In this tutorial, I show you:

• What survey weights actually mean
• Why NHANES uses complex sampling
• How to correctly build a survey design in R
• Why unweighted results can mislead you
• How to compute population-correct estimates

If you work with public datasets, health surveys, social research, or policy data — this is essential knowledge.

Watch now and level up your data analysis skills.

Comment “SURVEY” and I’ll send you more advanced R tutorials like this.