Reason about data and descriptive statistics in a practical context.
Means
Balancing
Distributions
Mean Values
Finding Totals
Predicting Means
Rebalancing
Asymmetric Distributions
Means of Lists
Splitting
Finding Means
Adding a Point
Updating Means
Comparisons
Median
Finding Medians
Splitting
Medians of Lists
Adding a Point
Comparing Median and Mean
Modes
Middle 50%
Segmenting Data
Quartiles
Interquartile Range
Quartiles of Lists
Boxplots
Adding Whiskers
Matching the Boxplot
The Range
Comparing Distributions
Outliers
Skewing the Mean
Defining Outliers
Identifying Outliers
Outside the Whiskers
Up next
Use probability to make better decisions.
Our journey begins with an interactive introduction to common measures of central tendency—mean, median, and mode. You’ll discover how these measures shift when you add new data or analyze entire datasets—using intuitive techniques that sidestep complex calculations. Next, we dive deeper into visualizing and comparing datasets—exploring variability (range, quartiles, and standard deviation) and examining how these measures reflect the shape of your data. By calculating quartiles, interpreting the interquartile range, and spotting outliers in boxplots, you’ll sharpen your analytical thinking and deepen your understanding of data behavior. This course equips you with essential data‑summary skills and visualization tools, fueling your STEM journey with strong data literacy and renewed confidence.