FY13CE Biology common mistakes
FY13CE Biology · Understand the traps and how to avoid them.
When predicting the products of a dihybrid cross, the candidate multiplies or adds the two single-gene ratios (for example concludes 9:3:3:1 by simply combining 3:1 and 3:1) without first confirming that the two genes assort independently, so linked or epistatic cases are scored with the wrong ratio.
The 9:3:3:1 ratio is memorized as a formula rather than derived from the product rule, so the candidate never checks the independence assumption that makes the product rule valid.
What to do instead
Before any dihybrid calculation, state the two conditions explicitly (genes on different chromosomes or far apart, and no interaction masking phenotypes). If either fails, build the gamete table from the actual linkage or interaction and derive the ratio instead of recalling it.
On pedigree and probability items, the candidate assigns a genotype to an unaffected individual as if the genotype were known (for example assumes a sibling of an affected child is a carrier) instead of computing a conditional probability from the parents' genotypes.
Unaffected individuals are visually identical in a pedigree, so the candidate treats 'no shading' as a single genotype rather than a set of possible genotypes whose relative likelihood must be calculated.
What to do instead
For every unaffected person, write the possible genotypes and their weights from the parents. For an autosomal recessive trait with carrier parents, the unaffected child is a carrier with probability 2/3, not 1/2. Show the denominator explicitly (probability of being unaffected) before dividing.
When reading a graph of enzyme rate versus substrate concentration or versus temperature, the candidate describes the trend ('it goes up then down') but does not attach the trend to a mechanism, so questions asking why the curve plateaus or falls are answered with restated graph shape.
Graph-reading is treated as a description task rather than an inference task, and the underlying causes (active-site saturation, denaturation, diffusion limits) are not linked to specific regions of the curve.
What to do instead
Annotate each region with its mechanism before answering: the plateau means all active sites are occupied (Vmax reached, adding substrate cannot help), and a post-optimum decline means denaturation of tertiary structure. Practice converting each labeled region into a one-sentence causal claim.
When explaining membrane transport or osmosis, the candidate says water 'wants to' move or that a solute 'pulls' water, and predicts direction from solute identity rather than from total solute concentration on each side, including cases with a permeable solute.
Everyday language about thirst and absorption reinforces a misleading mental model, and the candidate never sets up the concentration comparison explicitly on both sides of the membrane.
What to do instead
Before predicting direction, list total osmolarity on each side and mark which solutes can cross. Water moves toward higher total solute concentration only when the solute is impermeant. For a permeable solute, predict the eventual equilibration instead.
The candidate treats natural selection as a process that acts on individuals to produce needed changes during their lifetime, writing that an organism 'adapted in order to survive' or that a population 'mutated because it needed resistance'.
Teleological phrasing is common in textbooks and documentaries and is easy to absorb; the distinction between selection acting on existing variation across generations and individual acclimation is rarely practiced in writing.
What to do instead
Rewrite every explanation in three explicit steps: variation already present, differential reproductive success, change in allele frequency across generations. Ban the words 'in order to' and 'needed' from answers, and flag any sentence where a change happens within one organism's lifetime as acclimation, not evolution.
On Hardy-Weinberg items, the candidate uses p and q as the genotype frequencies (treating p as the frequency of homozygotes) or applies p squared plus 2pq plus q squared to a population that is small, nonrandomly mating, or under selection without noting that the model does not apply.
The symbols p and q are learned as labels for dominant and recessive rather than as allele frequencies, and the five assumptions are memorized as a list without being used as a validity checklist.
What to do instead
Always write the definitions at the top of the work: p equals frequency of one allele, q the other, p plus q equals 1. Convert phenotype counts to genotype counts first. Then state which assumptions hold; if any is violated, say the prediction is not valid rather than computing anyway.
When asked to design or critique an experiment, the candidate proposes a single treatment group with no control, or includes a control that differs from the treatment in more than one variable, and then attributes the result to the intended variable.
The candidate focuses on the hypothesis being tested and treats the control as a formality, so confounds and the need for a baseline comparison are not checked.
What to do instead
Use a checklist for every design: what is the independent variable, what is held constant, what is the negative control, what is the sample size, and what would the result look like if the hypothesis were false. Name at least one plausible confound and how the design rules it out.
The candidate confuses correlation with causation or treats a statistically significant difference as proof of biological importance, concluding that a treatment 'works' from a small mean difference without checking error bars, sample size, or effect size.
Significance testing language is encountered frequently but the distinction between statistical and practical significance, and between association and mechanism, is rarely made explicit in study materials.
What to do instead
For every data-interpretation item, answer three separate questions in writing: is there an association, is it likely due to chance (overlap of confidence intervals or error bars), and is the magnitude biologically meaningful. Only then consider a causal claim, and require a mechanism or a controlled manipulation.
When tracing energy flow or matter cycling in an ecosystem, the candidate treats energy and matter as interchangeable, saying energy is recycled or that nutrients flow through a food chain and are lost as heat, and misplaces the role of decomposers.
Food-chain diagrams usually show arrows for both energy and biomass without distinguishing them, so the two conservation rules are blurred.
What to do instead
State the two rules separately before answering: energy flows one way and is degraded to heat at each transfer (roughly 10 percent passed on), while matter cycles and is returned to abiotic pools by decomposers. Draw the nutrient arrow as a loop and the energy arrow as a one-way path.
When explaining physiological regulation, the candidate describes a negative feedback loop but omits the sensor and the effector, or reverses the direction of the response, producing an explanation in which the deviation is amplified rather than corrected.
Feedback is learned as a diagram with arrows rather than as a causal chain, so the candidate reproduces the shape of the loop without checking that each step opposes the initial change.
What to do instead
Write the loop as a sequence: stimulus, sensor, control center, effector, response, and then test it by asking whether the response reduces the original deviation. If it increases it, the loop is positive feedback and should be labeled as such.