3.3 Laboratory Procedures & Scientific Inquiry

Laboratory procedures and scientific inquiry are not a separate "extra" on the NLN NEX—they are woven through Biology and appear whenever a stem asks you to design a fair test, read a graph, choose units, or judge whether a conclusion matches the data. The Science section’s cognitive dimensions matter here: knowledge (definitions, equipment names), application (choose the right variable or control), and interpretation (extract meaning from tables, figures, and experimental summaries).

The Scientific Method

Science builds reliable knowledge through a cycle of questioning and testing. A practical sequence:

1. Observation / question — Notice a pattern or problem ("Do bean seedlings grow taller under blue light than under red light?")
2. Background research — Use existing knowledge to refine the question
3. Hypothesis — A testable, predictive statement, often in if–then form ("If seedlings receive blue light, then mean height after 14 days will be greater than under red light")
4. Experiment — Controlled procedure that generates data
5. Analysis — Organize results (tables, graphs, statistics)
6. Conclusion — Accept, reject, or revise the hypothesis; state limitations
7. Communication / replication — Others should be able to repeat the work

A hypothesis must be falsifiable—there must be a possible result that would show it is wrong. Opinions, value judgments, and supernatural claims are not scientific hypotheses in this sense.

Variables and Experimental Design

Sample size and replication reduce the chance that results are flukes. Random assignment (when feasible) and clear operational definitions (exactly how height is measured) improve quality.

Correlation is not causation. If two variables rise together in observational data, a third factor may drive both. Controlled experiments are stronger for causal claims; NEX interpretation items often test whether a conclusion overreaches the design.

Metric System and Measurement

Healthcare and laboratory science use the metric (SI) system.

Useful prefixes:

• kilo- (k) = 10³ (1 kg = 1000 g)
• centi- (c) = 10⁻² (100 cm = 1 m)
• milli- (m) = 10⁻³ (1000 mL = 1 L)
• micro- (µ) = 10⁻⁶ (1000 µL = 1 mL)

Convert carefully on calculation-style items: move the decimal when converting among milli/centi/base units. Measure with appropriate tools—graduated cylinder for liquid volume (read meniscus at eye level), electronic balance for mass, thermometer for temperature—and record units every time.

Microscopes

The compound light microscope is the workhorse of intro biology labs.

Total magnification = ocular magnification × objective magnification (e.g., 10× × 40× = 400×).

Good technique: start on low power, center the specimen, then move up in power; use fine focus only on high power; never use the coarse knob on high power in a way that drives the objective into the slide. Wet mounts use a coverslip at an angle to reduce air bubbles. Know that light microscopes have resolution limits; electron microscopes resolve much smaller structures but are not used on living specimens in standard school labs.

Common Lab Equipment

Besides microscopes and balances, recognize:

• Beakers and flasks — holding and mixing (approximate volumes)
• Pipettes / micropipettes — accurate small-volume transfer
• Test tubes and racks — small reactions and samples
• Petri dishes — culturing microorganisms on agar
• Hot plate / water bath — controlled heating
• pH paper or meter — acidity/alkalinity
• Centrifuge — separates components by density (advanced labs)
• Incubator — maintains temperature for cultures

Choose equipment that matches the precision needed: a beaker is fine for "about 100 mL of water for a water bath"; a graduated cylinder or pipette is better when volume is a measured variable.

Laboratory Safety

Safety is both professional habit and exam content:

• Wear PPE as required: goggles, gloves, lab coat
• Know locations of eyewash, shower, fire extinguisher, and exits
• Never eat, drink, or apply cosmetics in lab
• Tie back long hair; avoid dangling jewelry and open-toed shoes
• Read labels; never return unused chemicals to stock bottles
• Dispose of sharps, biohazard waste, and chemicals in designated containers only
• Report spills and injuries immediately; follow institutional protocols for blood and body fluids (nursing labs expand this under infection control)
• Wash hands before leaving

When a stem describes a student action (pipetting by mouth, heating a closed tube, tasting a solution), identify the hazard and the safer alternative.

Interpreting Graphs and Tables

Interpretation items reward slow reading:

1. Title — what relationship is claimed?
2. Axes — which variable is independent (often x) vs dependent (often y)? What units?
3. Scale — does it start at zero? Are intervals even?
4. Legend — multiple lines or bars?
5. Trend — increase, decrease, plateau, peak, inverse relationship?
6. Conclusion check — does the answer choice stick to the data, or invent a mechanism not shown?

Common graph types:

• Line graphs — continuous change over time or graded independent variable
• Bar graphs — comparing categories
• Tables — raw or summarized values; watch footnotes and sample sizes

Example trap: a graph shows enzyme activity rising with temperature up to 37 °C then falling. A valid conclusion is that activity peaks near 37 °C under the tested conditions. An invalid leap is "the enzyme is dead at all temperatures above 30 °C" if activity is still measurable above 30 °C.

Reliability and Validity (Basics)

You can have reliable but invalid measures (a scale that is always 2 kg high—consistent, wrong). Improving reliability may involve more trials, better instruments, and standardized procedures. Improving validity may require choosing a better dependent variable or removing confounders.

Accuracy (closeness to true value) and precision (closeness of repeated measurements to each other) are related ideas often paired with reliability discussions.

Aligning With NEX Cognitive Dimensions

• Knowledge: Define hypothesis, control, milliliter, total magnification
• Application: Given a research question, identify independent and dependent variables; pick appropriate glassware
• Interpretation: Read a data table on bacterial growth and choose the supported conclusion; spot an uncontrolled variable that weakens a claim

Practice by rewriting weak experiments into stronger ones: add a control group, hold constants steady, define the measurement, and match the conclusion to the evidence only. That habit transfers directly to clinical reasoning later—assess, intervene, reassess with data—but on NEX Science, stay grounded in the biology lab framework: fair tests, clear variables, metric sense, safe technique, and honest interpretation.