Types of Data

Learn to classify variables by type.

• Types of Data Explorer — Select a variable and see how it is classified: qualitative vs. quantitative, nominal vs. ordinal, discrete vs. continuous, and interval vs. ratio.

Sampling

Understand how different sampling methods work.

• Sampling Methods Explorer — Compare simple random, stratified, cluster, and systematic sampling. See how each method selects individuals from a population of 1000 employees.

Graphical Summaries

Visualize and summarize qualitative data.

• Frequency Distributions, Bar Graphs, and Pie Charts — Build frequency distributions from raw data or enter your own. Toggle between bar graphs and pie charts, and see how relative frequencies are calculated.
• Histogram Builder — Build histograms from preloaded datasets or enter your own data. Adjust the lower class limit and class width to see how these choices affect the histogram's shape. Includes examples of skewed, bell-shaped, bimodal, and uniform distributions.
• Visualizing Small Datasets — Explore dotplots and stem-and-leaf plots side by side. Toggle split stems, compare datasets with back-to-back plots, or upload your own data.

Descriptive Statistics

Visual demonstrations of measures of center and spread.

• Mean vs. Median with Outliers — Drag a point and watch the mean chase it while the median stays put. Demonstrates what "resistant" means.
• Skewness Explorer — Drag a slider to morph a distribution from left-skewed to symmetric to right-skewed. See how the mean is pulled toward the tail while the median stays closer to the center.
• Building Variance and Standard Deviation — Click data points one by one to see how each contributes to the variance formula. Shows why we square deviations and divide by n − 1.
• Comparing Values with z-Scores — See how z-scores place values from different distributions onto the same scale, enabling meaningful comparison.

Correlation and Regression

Explore relationships between two variables.

• Correlation Explorer — Drag points on a scatterplot and watch r update in real time. Add outliers to see why the correlation coefficient is not resistant.

Distributions

Explore probability distributions and their properties.

• Student's t Distribution vs. Standard Normal — See how the t distribution approaches the normal distribution as degrees of freedom increase.

Confidence Intervals

Understand what confidence really means through simulation.

• Confidence Intervals for a Mean — Generate many confidence intervals and see how often they capture μ. Demonstrates why "confidence" describes the method's success rate, not a probability about any single interval.
• Confidence Intervals for a Proportion — Generate many confidence intervals and see how often they capture p. Observe how sample size and the value of p affect coverage.