AP Biology · 13 Classic Lab Investigations ⚡ SPRINT MODE
Laboratory Investigations
AP Bio FRQs are almost always framed as experimental contexts. These 13 classic inquiry-based investigations are among the most commonly used to satisfy the AP Biology lab requirement — knowing each lab's hypothesis, IV, DV, control, and key calculation covers ~95% of what the exam tests from lab contexts.
Experimental DesignControls & Variables
Data Analysis% Change Calculations
Chi-SquareH-W Equations
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All 13 Labs
Quick Reference — 13 Classic Investigations at a Glance
Note: AP Biology requires 25% lab time for inquiry-based work. These 13 classic investigations are widely used to meet that requirement — they are not the only valid labs, but represent the most commonly assessed in exam contexts.
| Lab | Title | Unit Link | Key Concept Tested | Primary Data Analysis |
|---|---|---|---|---|
| INV 1 | Artificial Selection | Unit 7 | Heritable variation → phenotype shift over generations | Bar graph: mean ± SE per generation; compare selected vs. control |
| INV 2 | Mathematical Modeling | Unit 7 | Hardy-Weinberg: allele freq. under different evolutionary forces | p+q=1; p²+2pq+q²=1; start from q² |
| INV 3 | Comparing DNA Sequences | Unit 7 | Molecular evidence for evolution; constructing phylogenies | % DNA/AA similarity → relatedness; cladogram building |
| INV 4 | Diffusion & Osmosis | Unit 2 | Water potential; osmosis direction; solute concentration effects | % mass change = (final−initial)/initial × 100 |
| INV 5 | Photosynthesis | Unit 3 | Rate of photosynthesis vs. light intensity, CO₂, temperature | Floating leaf disk: time to 50% flotation (ET₅₀); rate vs. variable graphs |
| INV 6 | Cellular Respiration | Unit 3 | O₂ consumption by germinating seeds; temperature effects | Respirometer: O₂ consumption rate; subtract bead (non-living) control |
| INV 7 | Cell Division: Mitosis & Meiosis | Unit 4/5 | Phases of mitosis; mitotic index; crossing over in meiosis | Mitotic index = (cells in mitosis / total cells) × 100 |
| INV 8 | Bacterial Transformation | Unit 6 | Foreign DNA uptake; antibiotic resistance as selectable marker | Transformation efficiency = colonies / µg DNA; 4-plate comparison |
| INV 9 | Restriction Enzyme Analysis / Gel | Unit 6 | Restriction digest; gel electrophoresis fragment separation by size | Fragment size from gel: small = farther from wells; use ladder lane |
| INV 10 | Energy Dynamics | Unit 8 | Energy transfer efficiency between trophic levels | % energy transfer = (energy out / energy in) × 100 per trophic level |
| INV 11 | Transpiration | Unit 2 | Water loss via stomata; factors affecting transpiration rate | Potometer: water column distance moved per time; % change in leaf mass |
| INV 12 | Fruit Fly Behavior | Unit 8 | Taxis and kinesis; innate behavioral responses to stimuli | Choice chamber: % flies on each side; chi-square test vs. expected 50/50 |
| INV 13 | Enzyme Activity | Unit 3 | Effect of pH, temperature, substrate concentration on enzyme rate | Absorbance over time (colorimeter); initial rate = slope of early time points |
INV 1
Artificial Selection
Unit 7 — Natural Selection · Big Idea: Evolution
Setup
- Model organism: Wisconsin Fast Plants (Brassica rapa) or brine shrimp
- Trait: trichome density, seed weight, or similar heritable continuous trait
- IV: selection criterion (select high vs. select randomly)
- DV: mean trait value per generation
- Control: randomly mated group — same conditions, NO selection applied
Key Concepts & Exam Points
- If mean shifts in selected line → trait is heritable
- Demonstrates all 4 Darwinian postulates: variation, heritability, overproduction, differential reproduction
- Compare mean ± SE across generations; bar graph with error bars
- Response slows over time as genetic variation depleted
- Control must be randomly mated — NOT untreated plants
🎯 Exam Trap
The control for artificial selection is a randomly mated group (same conditions, random parent choice each generation). Without this control, you cannot attribute phenotypic change to selection — it could be environmental change or genetic drift. A "no treatment" group that doesn't reproduce is NOT an appropriate control here.
INV 2
Mathematical Modeling: Hardy-Weinberg
Unit 7 — Population Genetics · Big Idea: Evolution
Setup
- Method: Card/bead simulation or computer model — randomly draw alleles to simulate random mating
- Test violations: add selection (remove cards with aa), genetic drift (small vs. large populations), gene flow (exchange cards between populations), mutation
- Equations: p + q = 1; p² + 2pq + q² = 1
Key Concepts & Exam Points
- HWE is the null model — populations NOT evolving
- Start calculation from q² (recessive homozygote frequency)
- Small simulation → large drift; large simulation → stable near HWE
- Violating any of 5 conditions → deviation from HWE
- Never say "accept H₀" — say "fail to reject H₀"
🎯 Exam Trap
Always start from q² = frequency of individuals showing recessive phenotype → q = √q² → p = 1−q → 2pq = carrier frequency. Never start from dominant phenotype frequency — it includes both AA and Aa which you cannot separate without further calculation. Show all steps: each earns partial credit on FRQs.
INV 3
Comparing DNA Sequences to Investigate Evolutionary Relationships
Unit 7 — Evolution / Common Ancestry · Big Idea: Evolution
Setup
- Method: Use bioinformatics databases (BLAST, NCBI) to align DNA or protein (amino acid) sequences from multiple species
- Calculate percent identity / number of differences between species pairs
- Use similarity matrix to construct a cladogram (neighbor-joining or parsimony method)
Key Concepts & Exam Points
- More DNA/AA similarity → more recently shared common ancestor → more closely related
- Molecular data is more reliable than morphology (avoids convergent evolution confusion)
- Highly conserved sequences (e.g., cytochrome c, rRNA) = most useful across very distant taxa
- Universal genetic code = evidence all life shares common ancestry
- Cladogram topology: closer branch = more recent MRCA
🎯 Exam Trap
When comparing DNA sequences: more differences = less related (NOT more evolved). Two tips of a cladogram are always equally "evolved" — molecular clocks estimate divergence time, not evolutionary advancement. Always build your cladogram from % similarity data, not from assumptions about "which is more primitive."
INV 4
Diffusion & Osmosis
Unit 2 — Cell Transport · Big Idea: Cells
Setup
- Part A: Dialysis tubing (selectively permeable) filled with sucrose at various concentrations, placed in solutions → measure mass change
- Part B: Potato core or celery pieces placed in different sucrose concentrations → measure mass change
- IV: sucrose concentration of external solution
- DV: % mass change (NOT absolute mass change)
Key Concepts & Exam Points
- % mass change = (final − initial)/initial × 100 — must standardize; samples start at different masses
- Isotonic point: concentration where % mass change = 0 → solute concentration of tissue matches solution
- Hypotonic solution → mass increases (water enters); hypertonic → mass decreases (water exits)
- Water potential equation: Ψ = Ψs + Ψp; water flows high Ψ → low Ψ
- Graph % mass change vs. molarity → line crosses x-axis at isotonic concentration
🎯 Exam Trap
Always use % mass change, never absolute mass change. Two potato pieces starting at different masses will show different absolute changes even in the same solution — useless for comparison. % change normalizes for initial size. Also: "no mass change" = isotonic = this is the solute concentration inside the cells.
INV 5
Photosynthesis
Unit 3 — Cellular Energetics · Big Idea: Energy
Setup — Floating Leaf Disk Assay
- Vacuum-infiltrate leaf disks with bicarbonate solution (CO₂ source) → disks sink (air removed)
- Expose to varying light intensities, CO₂ concentrations, or temperatures
- Measure ET₅₀: time for 50% of disks to float (O₂ produced by photosynthesis restores buoyancy)
- IV: light intensity / CO₂ / temperature
- DV: rate of floating = 1/ET₅₀ (higher = faster photosynthesis)
Key Concepts & Exam Points
- Disks float because photosynthesis produces O₂ → replaces air removed by vacuum
- Dark control: disks remain sunk (no photosynthesis; respiration consumes O₂)
- Faster floating = more photosynthesis = more O₂ production
- Rate increases with: ↑ light, ↑ CO₂, ↑ temperature (up to optimum)
- Rate levels off at saturation point (limiting factor changes)
- Must include dark control to isolate photosynthesis from respiration
🎯 Exam Trap
The dark control (disks in bicarbonate, fully dark) shows baseline behavior — disks should remain sunk because O₂ is consumed by respiration and none produced. Without this control, you cannot attribute disk flotation specifically to photosynthesis. Also: rate = 1/time — shorter time to float = faster rate. Graph "number of floating disks over time" curves upward toward saturation.
INV 6
Cellular Respiration
Unit 3 — Cellular Energetics · Big Idea: Energy
Setup — Respirometer
- Germinating seeds in sealed syringe/tube with KOH (absorbs CO₂) and colored water indicator
- Three tubes: germinating seeds (warm), germinating seeds (cold), dead beads (control)
- Measure water column movement (O₂ consumed → gas volume decreases → indicator moves)
- IV: temperature (warm vs. cold) or germinating vs. non-germinating seeds
- DV: rate of O₂ consumption (mL/min per gram)
Key Concepts & Exam Points
- Subtract non-living bead control to get TRUE biological O₂ consumption rate
- Higher temperature → faster germination → faster respiration (up to optimum)
- Germinating seeds respire faster than dormant (more metabolic activity)
- KOH absorbs CO₂ so only O₂ consumption drives indicator movement
- Without KOH: CO₂ released = O₂ consumed → no net volume change → indicator wouldn't move
- Non-living bead control corrects for physical pressure/temperature changes
🎯 Exam Trap
You MUST subtract the non-living bead (dead seed) control from the experimental reading. The bead control accounts for physical changes in gas volume due to temperature, pressure, or handling — these are NOT due to respiration. Corrected rate = germinating seeds rate − bead control rate. Reporting raw rates without this correction overstates or understates true biological O₂ consumption.
INV 7
Cell Division: Mitosis & Meiosis
Units 4 & 5 — Cell Cycle / Heredity · Big Idea: Cells
Setup
- Mitosis: onion root tip or whitefish blastula slides → identify cells in each phase; count cells in each phase
- Meiosis: Sordaria fimicola (bread mold) ascospore patterns → count recombinant vs. non-recombinant asci → estimate map distance
- DV (mitosis): mitotic index = cells in mitosis / total cells × 100
Key Concepts & Exam Points
- Most cells in a root tip are in interphase (longest phase)
- Mitotic index ↑ in rapidly dividing tissue (tip of root); ↓ in mature tissue
- Sordaria recombination: non-recombinant asci = 4+4 pattern; recombinant = 2+2+2+2 pattern
- % recombination = (# recombinant asci / total asci) × 100; divide by 2 for map distance (cM)
- Identify mitotic phases: prophase (chromatin condenses), metaphase (aligned), anaphase (separating), telophase (two nuclei)
🎯 Exam Trap
Mitotic index calculation: only count cells actually in mitosis (any of PMAT phases), NOT all cells with visible chromosomes. Interphase cells are the majority — they should NOT be counted in the numerator. For Sordaria: divide recombination percentage by 2 to get the map distance in centimorgans (because crossing over between homologs affects only 2 of 4 chromatids).
INV 8
Bacterial Transformation
Unit 6 — Gene Expression · Big Idea: Information
Setup — 4 Plates
- Transform E. coli with plasmid carrying ampicillin resistance gene (ampR) and GFP gene
- Plate 1: +DNA, +ampicillin → only transformed bacteria grow (ampR + GFP); shows transformation success
- Plate 2: +DNA, no ampicillin → all bacteria grow (bacterial lawn)
- Plate 3: −DNA, +ampicillin → no colonies (control — confirms amp kills non-transformed bacteria)
- Plate 4: −DNA, no ampicillin → bacterial lawn (confirms bacteria were viable)
Key Concepts & Exam Points
- Transformation efficiency = number of colonies on +amp plate / µg of DNA added
- GFP (green fluorescent protein): transformed cells glow green under UV light
- Selective marker: antibiotic resistance gene allows selection of transformed cells only
- Only bacteria that took up plasmid survive on amp plate
- Colonies on +amp/+DNA plate = number of successful transformation events
- No colonies on −DNA/+amp plate = expected negative control (not failure)
🎯 Exam Trap
No colonies on the –DNA/+amp plate is the EXPECTED result (the control works correctly). It does NOT mean "no bacteria were present" — Plate 4 (–DNA/no amp) should show a bacterial lawn confirming bacteria were viable. "No colonies on amp plate" = no transformed bacteria; it says nothing about whether untransformed bacteria exist. Always interpret all 4 plates together.
INV 9
Restriction Enzyme Analysis & Gel Electrophoresis
Unit 6 — Biotechnology · Big Idea: Information
Setup
- Digest DNA samples with restriction enzymes → cut at specific palindromic sequences
- Run products on agarose gel; DNA migrates toward positive electrode
- Wells at TOP; DNA moves DOWN; small = faster = farther from wells
- DNA ladder: known-size fragments in one lane; used to estimate unknown fragment sizes
- Stain with ethidium bromide or similar dye → visualize bands under UV
Key Concepts & Exam Points
- Smaller fragments travel FARTHER (faster) through gel
- Number of bands = number of fragments from restriction digest = number of cut sites + 1 (for circular DNA: = number of cut sites)
- DNA fingerprinting: compare band patterns between samples
- RFLP analysis: restriction fragment length polymorphisms → identify individuals or alleles
- Fragment size × number of cut sites → total = original plasmid size
🎯 Exam Trap
Smaller fragments migrate FARTHER from the wells — not larger ones. Bands near the bottom of the gel = small DNA fragments. Bands near the top (near wells) = large fragments. Also: if 2 bands appear after digestion of a circular plasmid, it has exactly 2 restriction cut sites. The sum of all band sizes should equal the total plasmid size.
INV 10
Energy Dynamics
Unit 8 — Ecology · Big Idea: Interactions
Setup
- Measure energy content (using calorimetry or biomass data) at each trophic level in a model ecosystem
- Often uses Wisconsin Fast Plants as producers, herbivorous insects as primary consumers
- Measure: dry mass or caloric content at producer and consumer level
- IV: trophic level
- DV: energy content (kcal) or biomass (g) per unit area
Key Concepts & Exam Points
- % energy transfer = (energy at higher level / energy at lower level) × 100
- Expect ~10% transfer efficiency (10% rule)
- Energy at each level < energy at level below
- Endotherms (birds, mammals) are less efficient consumers than ectotherms → need more food energy
- Pyramid of biomass and energy both narrow at top
- Energy flows one way; matter cycles
🎯 Exam Trap
Calculate % energy transfer correctly: if producers have 1,000 kcal and primary consumers have 80 kcal, the transfer efficiency is 80/1000 × 100 = 8% (close to 10% rule). Do NOT confuse biomass pyramid with numbers pyramid — a large biomass of phytoplankton can support a smaller number of large fish even if fish are bigger individually.
INV 11
Transpiration
Unit 2 — Cell Transport · Big Idea: Cells
Setup — Potometer
- Cut plant stem underwater, attach to potometer (sealed water column + air bubble)
- Measure rate of air bubble movement = rate of water uptake (approximates transpiration)
- Test: fan (wind), high humidity, high temperature, petroleum jelly on leaves (blocks stomata)
- IV: environmental condition (wind, humidity, temperature, light)
- DV: rate of bubble movement (cm/min) OR % change in leaf mass
Key Concepts & Exam Points
- Transpiration driven by: cohesion-tension; evaporation from mesophyll → stomata → atmosphere
- ↑ wind/fan → ↑ transpiration (removes humid air near stomata)
- ↑ humidity → ↓ transpiration (smaller water vapor gradient)
- ↑ temperature → ↑ transpiration (higher evaporation rate)
- Light → stomata open → ↑ transpiration; dark → stomata close → ↓ transpiration
- Petroleum jelly on lower leaf surface (most stomata) dramatically ↓ transpiration
🎯 Exam Trap
Students often think humidity INCREASES transpiration because "there's more water in the air." Wrong — high humidity reduces the water vapor concentration gradient between leaf and atmosphere, so less water evaporates from the leaf. Low humidity (dry air) → steep gradient → more transpiration. Also: stomata are mainly on the LOWER (abaxial) surface of leaves — sealing the bottom surface matters more than sealing the top.
INV 12
Fruit Fly Behavior
Unit 8 — Ecology / Behavior · Big Idea: Interactions
Setup — Choice Chamber
- Drosophila melanogaster placed in a T-maze or choice chamber with two contrasting conditions (light/dark; moist/dry; food/no food)
- Count flies on each side after a set period
- IV: type of stimulus (light, moisture, chemical)
- DV: % flies choosing each side; preference index
- Control: chamber with both sides identical (expected 50/50)
Key Concepts & Exam Points
- Positive taxis: directed movement TOWARD stimulus (phototaxis toward light)
- Kinesis: undirected change in movement speed/turning rate (NOT direction)
- Chi-square test: compare observed distribution to expected 50/50 split; df = 1; critical value = 3.841
- If χ² > 3.841 → reject H₀ (significant preference exists)
- If χ² < 3.841 → fail to reject H₀ (distribution consistent with no preference)
- Replicate with many flies and multiple trials to reduce sampling error
🎯 Exam Trap
For the chi-square in fruit fly behavior, the expected distribution under H₀ is 50% on each side (equal preference = null hypothesis). If 30 flies are used and 22 go to the light side, observed = [22, 8], expected = [15, 15]. χ² = (22−15)²/15 + (8−15)²/15 = 3.27 + 3.27 = 6.53 > 3.841 → reject H₀ → flies show a significant preference for light. Remember: fail to reject ≠ accept.
INV 13
Enzyme Activity (Catalase / Peroxidase)
Unit 3 — Cellular Energetics / Enzymes · Big Idea: Energy
Setup
- Enzyme (catalase from turnip/liver OR peroxidase from horseradish) + substrate (H₂O₂ or ABTS)
- Measure absorbance over time using spectrophotometer/colorimeter
- Test effects of: pH, temperature, substrate concentration, inhibitor
- IV: pH / temperature / [substrate] / inhibitor presence
- DV: absorbance change per unit time = enzyme activity rate
Key Concepts & Exam Points
- Initial rate = slope of early time points (before substrate depletes or product inhibits)
- Do NOT use total change at endpoint — enzyme activity decreases over time
- Optimal pH and temperature: rate peaks, then falls sharply (denaturation above optimum)
- Denaturation is usually irreversible; cold slows but does not denature (reversible)
- Include a boiled enzyme control: denatured enzyme, no activity → confirms observed activity is biological
- Blank/buffer control: no enzyme → any absorbance change is non-enzymatic
🎯 Exam Trap
Always use INITIAL RATE (slope of first few data points), not endpoint measurement. Enzyme activity is highest at the start when substrate is abundant. As time progresses, substrate depletes and product may inhibit — the curve flattens. Measuring total change at a fixed time point underestimates Vmax and gives a non-linear result. Show your calculation: Δabsorbance / Δtime = initial rate.
A student measures catalase activity at 5 different pH values (4, 6, 8, 10, 12). She measures absorbance at t = 0 and t = 5 minutes, and records total change. Her data show maximum activity at pH 8. A classmate argues the experimental design is flawed. What is the most likely flaw, and how should the experiment be corrected?
- (A) She should have used more concentrations of H₂O₂ substrate
- (B) She measured total change at 5 min instead of initial rate — the enzyme may have been depleted at different rates at different pHs, making the comparison invalid
- (C) She should have included a positive control with higher pH
- (D) Catalase does not work at neutral pH, so the design is biologically flawed
Answer: (B) — Endpoint measurement (total change at 5 min) is not a reliable measure of enzyme activity rate. At high pH (optimum), the enzyme may consume all substrate within 2 minutes, after which the absorbance plateaus. At low pH, the enzyme works slowly and is still active at 5 min. The 5-min total change would falsely underestimate activity at the optimum (substrate already exhausted). The correct approach is to measure absorbance every 30 seconds, plot absorbance vs. time for each pH, and calculate the initial rate (slope of the linear phase) for each curve. This gives a true comparison of reaction rates.
Science Practices
AP Biology Science Practices — Quick Reference
| Practice | What It Means | Exam Application |
|---|---|---|
| SP 1 Models & Representations | Describe, create, and interpret visual representations (diagrams, graphs, cladograms, models) | Reading/constructing graphs; interpreting cladograms; drawing experimental setups |
| SP 2 Quantitative Skills | Use mathematical reasoning; calculate rates, percentages, ratios; apply formulas | % mass change; H-W calculations; chi-square; 10% energy rule; mitotic index; water potential |
| SP 3 Scientific Questions | Pose, refine, and evaluate scientific questions; formulate testable hypotheses | FRQ: "design an experiment to test..." — identify testable, falsifiable hypothesis |
| SP 4 Data Collection & Experimental Design | Plan and conduct investigations; identify IV, DV, controls, replicates; minimize sources of error | FRQ design questions: state IV, DV, control, method of measurement, expected results |
| SP 5 Data Analysis & Evaluation | Analyze and interpret data; identify trends, patterns, anomalies; draw evidence-based conclusions | Interpreting graphs; identifying which variable explains a trend; describing what data support/refute |
| SP 6 Scientific Argumentation | Construct, support, and refute scientific claims using evidence; evaluate alternative explanations | FRQ conclusions: "the data support/do not support the hypothesis because..." + specific evidence cited |
⚡ Experimental Design FRQ Template
- 1. State hypothesis: "If [independent variable] is increased, then [dependent variable] will [increase/decrease] because [biological mechanism]."
- 2. Identify IV: The single variable you change (e.g., temperature, concentration, presence/absence of inhibitor)
- 3. Identify DV: What you measure (e.g., enzyme activity rate, % mass change, number of colonies)
- 4. Controlled variables: Everything else kept constant (temperature, pH, volume, time, organism)
- 5. Control group: No treatment applied to the IV (e.g., 0 concentration, no inhibitor, room temperature) — establishes baseline
- 6. How to measure DV: Specific method (colorimeter for absorbance, balance for mass, ruler for distance)
- 7. Expected results if hypothesis is correct: "If correct, then [treated group] will show [greater/less] [DV] than [control group]"
- 8. Replicates: Mention multiple trials or sample size to reduce random error
⚠ Lab Trap Alert
High-Frequency Lab Errors to Avoid
- 📊INV 4 (Osmosis): Use % mass change, NOT absolute mass changeSamples start at different masses — absolute change is not comparable. Always: % change = (final − initial)/initial × 100. This normalizes across samples. A potato gaining 0.5g starting from 2g is very different from gaining 0.5g starting from 8g.
- 🎯INV 6 (Respiration): MUST subtract the non-living bead controlThe bead control corrects for physical changes in gas volume from temperature or pressure fluctuations in the water bath — NOT due to biology. Corrected rate = germinating seeds rate − bead rate. Reporting raw data without subtraction overstates or distorts the true biological O₂ consumption rate.
- 🔬INV 13 (Enzyme): Use INITIAL rate, not total change at endpointEnzyme activity is highest early when substrate is abundant. As time passes, substrate depletes and product inhibits. The curve flattens. Measuring total change at a fixed time gives a rate distorted by depletion. Initial rate = slope of the first few (linear) time points on the absorbance vs. time graph.
- 🧫INV 8 (Transformation): No colonies on −DNA/+amp plate is EXPECTED — not a failureThis is the negative control working correctly: bacteria without the plasmid die on ampicillin medium. It does NOT mean bacteria were absent — Plate 4 (−DNA/no amp) shows a lawn confirming bacteria were viable. Interpret all 4 plates together as a system: only the +DNA/+amp plate shows successful transformation events.
- ➡️INV 9 (Gel): Smaller fragments travel FARTHER (not larger)Smaller DNA fragments move faster through the agarose gel matrix and travel farther from the wells. Bands near the bottom = small. Bands near the wells (top) = large. Students who reverse this will misread every gel electrophoresis data question.
- 🧮INV 2 / INV 12: "Fail to reject H₀" — NEVER "accept H₀"In statistics, H₀ is never accepted or proven — only rejected or not rejected. "Fail to reject H₀" means insufficient evidence to conclude the null is false. This applies to both Hardy-Weinberg chi-square analysis (INV 2) and fruit fly choice behavior (INV 12). Writing "accept H₀" costs points on every FRQ.
- 🌿INV 5 (Photosynthesis): Must include a dark control for floating leaf disk assayThe dark control shows that disks in bicarbonate in complete darkness do NOT float (or re-sink if initially floating) — because only cellular respiration occurs, consuming O₂. Without this control, you cannot attribute disk floating specifically to photosynthetic O₂ production. It separates photosynthesis from background O₂ changes.
- 💧INV 11 (Transpiration): High humidity DECREASES transpiration — not increasesHigh humidity reduces the water vapor concentration gradient between leaf interior and atmosphere → less driving force for evaporation → less transpiration. Low humidity (dry air) → steep gradient → more transpiration. This is the opposite of what students often assume.
✓ Last-Min Checklist
Labs Pre-Exam Checklist
Click each item to confirm. These are the most-tested lab concepts.
- INV 1: Control = randomly mated group (same conditions, no selection); response to selection = heritability confirmed
- INV 2: H-W start from q² (recessive phenotype) → q → p → 2pq (carriers); "fail to reject H₀" never "accept"
- INV 3: More DNA similarity = more closely related; molecular data > morphology for phylogenetics
- INV 4: % mass change = (final−initial)/initial × 100; isotonic = 0% change; NEVER use absolute change
- INV 5: Floating disks = O₂ from photosynthesis; rate = 1/ET₅₀; dark control required
- INV 6: Subtract bead (non-living) control from germinating seeds rate; KOH absorbs CO₂ so only O₂ consumption measured
- INV 7: Mitotic index = (cells in mitosis / total cells) × 100; Sordaria: % recombination ÷ 2 = map distance (cM)
- INV 8: No colonies on −DNA/+amp = EXPECTED (negative control); transformation efficiency = colonies/µg DNA
- INV 9: Small fragments = farther from wells on gel; bands sum = original DNA size; 2 bands = 2 cut sites on circular DNA
- INV 10: % energy transfer = (higher level / lower level) × 100; ~10% per level
- INV 11: High humidity → ↓ transpiration (reduced gradient); fan → ↑ transpiration; stomata mostly on lower leaf surface
- INV 12: Chi-square for behavior: expected = 50/50; df=1; critical value = 3.841; "fail to reject" not "accept"
- INV 13: Use INITIAL rate (early slope), not endpoint; include boiled enzyme control; cold = slow (reversible), heat = denatured (irreversible)
⚡ Lab FRQ Strategy — Last Reminder
- Experimental design FRQs always need: hypothesis + IV + DV + controlled variables + control group + measurement method + expected result. Missing any = missing points
- Data analysis FRQs: Always describe the trend first ("as X increases, Y increases/decreases"), then explain the biological mechanism, then draw a conclusion about the hypothesis
- Statistics: Chi-square "fail to reject H₀" phrasing is mandatory. State the p-value context: "at p = 0.05 with df = [X], the critical value is [Y]. Since χ² = [Z] is [less/greater] than [Y], we [fail to reject/reject] H₀"
- Controls: Every experiment needs a negative control (no treatment). Some need a positive control (known effect). The control removes confounding variables and validates that your experimental system works