Some features come in neat boxes — you are blood group A or you are not. Others come in a smooth range, like height. The difference is not just a labelling exercise: it tells you how many genes are involved and how much the environment is doing.
📚 What you need to know
Discrete (discontinuous) variation falls into clear-cut categories with nothing in between — blood group, tongue rolling.
Continuous variation gives a full range of values between two extremes — height, body mass, milk yield.
Discrete variation is usually controlled by one gene and barely affected by the environment.
Continuous variation is polygenic: many genes each add a small amount, and the environment shifts the result too.
Polygenic features plotted for a whole population usually give a normal distribution — a bell-shaped curve.
A box plot shows five values: lowest, first quartile, median, third quartile, highest. An outlier lies more than 1.5 × IQR beyond a quartile.
Two kinds of variation
Ask yourself one question: can a value fall between two of the categories?
Blood group cannot. You are A, B, AB or O — there is no “slightly A”. That is discrete variation, and one gene decides it.
Height can. Between 168 cm and 169 cm there are endless possible values, limited only by how precisely you measure. That is continuous variation.
The trap: shoe size. Shoe sizes look like neat categories, but feet do not actually come in steps. Manufacturers group a smooth range into sizes for convenience. The underlying variation is continuous — only the measurement is grouped.
Feature
Continuous variation
Discrete variation
Range of values
Any value between two extremes
A few separate categories only
Genes involved
Many loci, often on different chromosomes
Usually one locus
Type of data
Quantitative — measured
Qualitative — counted or named
Effect of environment
Large
Little or none
Typical graph
Histogram with a bell-shaped curve
Bar chart or pie chart with gaps
Examples
Height, body mass, milk yield in cattle
Blood group, tongue rolling
Why many genes give a smooth range
Work it through with numbers. One gene with two alleles gives at most three genotypes and three possible phenotypes. Add a second gene and you get nine combinations. Add a third and you have twenty-seven.
Each allele adds only a small amount to the feature, and the effects add up — this is called an additive effect. With enough genes the steps between neighbouring phenotypes become too small to notice, and the feature looks continuous. Genes that work together like this are called polygenes.
Then the environment blurs the picture further. Skin colour depends on several genes controlling melanin production, and on how much UV light you are exposed to. Height depends on many genes, plus diet and childhood health.
The idea in one line
many genes + small additive effects + environment = a smooth range
The bars touch. That is the visual signature of continuous data — a bar chart of discrete data has gaps between the bars.
If a graph question asks you to “identify the type of variation”, look at the axis, not the biology. A measured x-axis with touching bars means continuous. Named categories with gaps means discrete.
Box plots
A box plot (or box-and-whisker diagram) is a quick way to summarise a large data set. It needs five numbers:
Lowest value — the start of the left whisker
First quartile (Q1) — 25% of the data lies below this
Median — the middle value, drawn as a line inside the box
Third quartile (Q3) — 75% of the data lies below this
Highest value — the end of the right whisker
The box holds the middle 50% of the data, so its width is the interquartile range (IQR = Q3 − Q1). Each whisker holds 25% of the data. The median does not have to sit in the centre of the box — if it does not, the data is skewed.
Notice the median sits left of centre in the box, so the upper half of the middle 50% is more spread out than the lower half.
Worked examples
WORKED EXAMPLE 1
For the box plot above, calculate the range and the interquartile range, and state which one is less affected by extreme values.
Step 1: read the five values
min 152, Q1 161, median 166, Q3 172, max 181
Step 2: range181 − 152 = 29Step 3: interquartile rangeIQR = 172 − 161 = 11Range 29, IQR 11 — the IQR is less affectedThe IQR ignores the top and bottom 25%, so one unusual value cannot distort it. That is why it is the better measure of spread here.
WORKED EXAMPLE 2
Using the same data, show that the value 143 is an outlier.
Step 1: state the rule
A value is an outlier if it lies more than 1.5 × IQR below Q1 or above Q3
Step 2: calculate 1.5 × IQR1.5 × 11 = 16.5Step 3: find the lower boundary161 − 16.5 = 144.5Step 4: compare143 is below 144.5143 is an outlier, so it is plotted separatelyFor completeness the upper boundary is 172 + 16.5 = 188.5, and nothing in this data set is above it.
💡 Exam tip
Say “polygenic” and “additive” when you explain continuous variation — those are the words the mark scheme wants.
Mention the environment too. Continuous variation questions almost always want genotype and environment.
Show your working for outliers. Write the 1.5 × IQR calculation and the boundary before you judge the value.
Use graph paper properly if asked to draw a box plot: even scale, five short vertical lines, box joined up, outliers plotted separately.
Quote a named example of each type of variation rather than describing them in general terms.
⚠ Common mix-up
Calling shoe size discrete variation. The data is grouped, but foot length varies continuously.
Saying continuous variation is “caused by the environment”. Genes cause it; the environment modifies it.
Assuming the median sits in the middle of the box. It often does not, and that tells you something.
Drawing whiskers out to the outlier. Outliers go outside the whiskers, as separate points.
Confusing range with IQR. Range uses the extremes; IQR uses the quartiles.
Leaving gaps between histogram bars when the data is continuous. Touching bars are part of the answer.
Up next: Dihybrid Crosses & Unlinked Genes — two genes at once, independent assortment, and where 9 : 3 : 3 : 1 actually comes from.
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