A stem-and-leaf plot (stemplot) is a display of quantitative data that splits each value into a stem (leading digits) and a leaf (final digit), preserving every original data value while showing the distribution's shape, center, variability, and outliers.
A stem-and-leaf plot, often called a stemplot, organizes quantitative data by splitting each value into two pieces. The stem holds the leading digit or digits, and the leaf holds the final digit. So the value 47 becomes a stem of 4 with a leaf of 7. Stack all the leaves next to their stems in order, and you get something that looks like a sideways histogram, except you can still read off every single original value.
That last part is the whole point. A histogram lumps values into bins and throws away the individual numbers. A stemplot keeps them. You can find the exact median, spot the exact maximum, and count exact values, all from the graph itself. For comparing two groups, a back-to-back stemplot puts one group's leaves on the left of a shared stem and the other group's leaves on the right, which makes it easy to compare shape, center, variability, and outliers side by side. That comparison skill is exactly what Topic 1.9 is about.
Stem-and-leaf plots live in Unit 1 (Exploring One-Variable Data), specifically Topic 1.9, Comparing Distributions of a Quantitative Variable. They directly support learning objective AP Stats 1.9.A, which asks you to compare graphical representations for multiple sets of quantitative data on center, variability, clusters, gaps, outliers, and other features. They also feed into 1.9.B, since a stemplot lets you pull exact summary statistics (like the median) straight from the display. On the exam, a back-to-back stemplot is one of the College Board's favorite ways to hand you two distributions and say 'compare these.' If you can read a stemplot quickly and describe both groups using SOCS (shape, outliers, center, spread) with context, you've covered one of the most reliable FRQ setups in the course.
Keep studying AP Statistics Unit 1
Histogram (Unit 1)
A stemplot is basically a histogram rotated sideways where the bars are made of actual digits. Each stem acts like a bin, but unlike a histogram, you never lose the individual data values. Use a stemplot for small datasets, a histogram for large ones.
Median (Unit 1)
Because a stemplot keeps every value in order, you can count in from the ends and find the exact median. A histogram only lets you estimate which bin the median falls in, so exam questions that ask for a precise center often hand you a stemplot.
Box Plot (Unit 1)
Side-by-side boxplots and back-to-back stemplots are the two classic tools for comparing groups in Topic 1.9. The trade-off runs the same direction both times. Boxplots summarize with five numbers and show outliers cleanly, while stemplots show every value and reveal clusters and gaps a boxplot hides.
Skewness (Unit 1)
Shape is usually the first thing you read off a stemplot. A long tail of leaves trailing toward the high stems means the distribution is skewed to the right, which in turn tells you the mean gets pulled above the median.
Stemplots show up on both multiple choice and FRQs, almost always in a comparison setting. The 2026 FRQ Q1 is the classic format. A goat farmer takes independent random samples of 14 goats from two breeds and you compare the weight distributions, hitting shape, center, variability, and outliers, with context (actual weights in pounds, actual breed names) in every sentence. Practice questions follow the same pattern, asking things like what clustering in the 20s and 30s tells you about one group, or which feature to examine first when comparing two stemplots. Three habits earn points here. Use comparative language (Breed H's median weight is higher than Breed J's), not two separate descriptions. Pull exact values when the question asks for them, since the stemplot preserves the raw data. And always check the key, because a stem of 4 and leaf of 7 could mean 47 or 4.7 depending on the units.
Both show the distribution of one quantitative variable, and a stemplot even looks like a histogram turned on its side. The difference is what survives. A histogram groups data into bins, so you only know how many values fall in each interval, not what they are. A stemplot keeps every original value visible, so you can compute exact statistics like the median directly from the graph. Histograms scale to thousands of data points; stemplots get unreadable past a few dozen values.
A stem-and-leaf plot splits each data value into a stem (leading digits) and a leaf (final digit), so the value 53 becomes stem 5, leaf 3.
Unlike a histogram, a stemplot preserves every original data value, which means you can find the exact median, minimum, and maximum from the graph.
A back-to-back stemplot shares one column of stems between two groups and is a standard exam setup for comparing distributions under Topic 1.9.
When comparing stemplots on an FRQ, address shape, outliers, center, and spread (SOCS), use comparative language like 'higher than' or 'more spread out than,' and include the context of the data.
Always read the key on a stemplot, because the same stems and leaves can represent 47 pounds or 4.7 pounds depending on how the plot is defined.
Stemplots work best for small datasets (roughly under 50 values); for large datasets, a histogram or boxplot is the better choice.
It's a display of quantitative data where each value is split into a stem (the leading digits) and a leaf (the final digit), with leaves stacked in order next to their stems. It shows the distribution's shape while keeping every original data value readable, and it's tested in Topic 1.9 of Unit 1.
No. A stemplot looks like a sideways histogram, but a histogram bins the data and discards individual values, while a stemplot keeps every value visible. That's why you can find the exact median from a stemplot but only estimate it from a histogram.
Yes, exactly. Since the leaves are listed in order, you count in from either end to the middle value (or average the two middle values for an even count). With 14 values, like the goat samples in the 2026 FRQ, the median is the average of the 7th and 8th values.
It's a stemplot where two groups share one column of stems, with one group's leaves extending left and the other's extending right. It's the standard way exam questions present two small samples for comparison, like two breeds of goats or two regions' test scores.
Yes. The 2026 exam's FRQ Q1 used independent samples of 14 goats from two breeds and asked for a comparison of the weight distributions. The scoring rewards comparing center, variability, shape, and outliers with comparative language and context, not just describing each group separately.