Continuous Variation: Skills (DP IB Biology)

Continuous Variation

Variation can be discrete or continuous

• Discrete variation is variation that falls into two or more clear-cut categories with no overlap or in-between categories

  • Blood group is an example of discrete variation

  • All human blood is either group O, A, B or AB, each with a Rhesus factor (+ or -)

• This gives just 8 distinct blood groups:

Pie chart showing global blood group distribution

Worldwide A, B, O blood group distribution by percentage, 2019

(data varies regionally with ethnicity)

Continuous Variation

• Continuous variation occurs when two or more genes affect the final characteristic

• For example, height in humans is determined by many genetic factors:

  • Bone length

  • Skeletal muscle structure

  • Ability to absorb food substances effectively

  • Hormone production

  • …As well as environmental factors like diet, exercise, prenatal nutrition, lifestyle etc

• Most characteristics are determined by more than one gene - a polygenic characteristic

• Even grouped data like shoe size appears to be discrete but in fact, peoples' feet vary continuously in size

  • Shoe size is merely a practicality for shoe manufacturers, who cannot make exactly the right-sized shoes for everybody

• Continuous variation in birth mass results in the population displaying a normal distribution (bell-shaped curve)

  • Environmental factors can also affect birth mass, e.g. mother's diet, presence of a twin, smoking etc

• Continuous variation occurs when there are quantitative differences in the phenotypes of individuals within a population for particular characteristics

• Quantitative differences do not fall into discrete categories like in discontinuous variation

  • For example, the mass or height of a human is an example of continuous variation

  • Instead for these features, a range of values exist between two extremes within which the phenotype will fall

• The lack of categories and the presence of a range of values can be used to identify continuous variation when it is presented in a table or graph

Normal distribution curve

Graph showing population variation in height: an example of continuous variation with quantitative differences

Genetic basis of continuous variation

• This type of variation is caused by an interaction between genetics and the environment

• Phenotype = genotype + environment

• At the genetic level:

  • Different alleles at a single locus have a small effect on the phenotype

  • Different genes can have the same effect on the phenotype and these add together to have an additive effect

  • If a large number of genes have a combined effect on the phenotype they are known as polygenes

• An example of a continuous polygenic trait is skin colour

• Skin colour is determined by several genes that cause the production of a protein called melanin

  • The more melanin is produced, the darker the skin pigmentation becomes

• Skin colour is also influenced by environmental factors such as UV exposure, which can cause the skin colour to become darker

Comparison of Continuous and Discontinuous Variation Table

Box & Whisker Plots

What are box plots and when should they be used?

• Box plots are also known as box-and-whisker diagrams

• They are used when we are interested in splitting data up into quartiles

• Using quartiles and drawing a box plot allows us to see what is happening at the low, middle and high points and consider any possible extreme values

How to draw a box plot

• You need to know five values to draw a box plot

  • Lowest data value

  • First quartile

  • Median

  • Third quartile

  • Highest data value

• Usually on graph paper, box plots are drawn accurately with the five points marked by short vertical lines

  • The middle three values then form a box with the median line inside

    • The median will not necessarily be in the middle of the box

  • The box represents the interquartile range (middle 50% of the data)

  • The lowest data value and highest data value are joined to the box by horizontal lines

    • These are often called whiskers

    • They represent the lowest 25% of the data and the highest 25% of the data

• You may be given a box plot

  • From which you can read off the five values

  • Calculate other statistics like the range and interquartile range (IQR)

Outliers

• Outliers are data points that exist at the extremes above and below the rest of the data

• In order for a data point to be categorised as an outlier it needs to be more than 1.5 × the interquartile range above the third quartile or below the first quartile

• As shown in the worked example above, the outliers are plotted separately to the whiskers of the plot