Marine Science Practical Skills and Data Analysis

Experimental planning

• Steps:

  • Observe qualitatively (descriptive) rather than quantitatively.

  • Hypothesis: possible explanation to answer 'why?'.

  • Prediction: what you think will happen, linked to the hypothesis.

  • Design experiment to test hypothesis with quantitative data.

• Key concepts to include in any experiment:

  • Independent variable (manipulated): what you change.

  • Dependent variable (measured): what you observe.

  • Control variables/constants: kept the same (e.g., temperature, CO₂, O₂, pH, light).

  • Confounding variables: not fully controllable; must be recorded/measured as they can affect results.

  • Control group/experiment: treated the same as experimental group but without the independent variable.

  • Safety and ethics: assess hazards/risks; treat living organisms ethically.

Choosing appropriate techniques and controlling variables

• Techniques to control key variables:

  • Temperature: use a water bath; thermostatically controlled units; keep constant with thermometer.

  • pH: use a buffer to maintain constant pH.

  • Oxygen: bubble into solution with an air pump.

  • Carbon dioxide: use hydrogen carbonate solution to raise CO₂ levels.

  • Light: keep equal distance from light source.

• Lab description: be able to describe how to control key variables in your experiment.

Measuring and equipment

• Measurements and typical equipment:

  • Liquid volume: graduated cylinder

  • Mass: balance or weighing scale.

  • Temperature: thermometer.

  • Time: stopwatch.

  • pH: pH probe or universal indicator.

• Use correct equipment and units for each measurement.

Experimental design: data points and repeats

• Determine how many measurements/observations to take:

  • Choose range with at least 5 values for the independent variable.

  • For each value, take at least 3 readings (trials) to identify anomalies.

  • Do not include anomalous results when calculating the mean.

Data presentation and observations (data tables)

• Data table structure:

  • Columns: Independent variable with units; Dependent variable with units; Trials (e.g., Trial 1, Trial 2, Trial 3); Average/Mean.

  • If calculating averages, include an average column.

  • Record results with consistent precision (same decimal places)

Drawing and data presentation: figures and diagrams

• Practice drawings (sea star, snapper) emphasize accurate proportions and scale; use ruler-drawn labels without arrowheads.

Graphs: general rules

• Graph basics:

  • Independent variable on the X-axis; dependent variable on the Y-axis.

  • Axes labeled with description and units.

  • Use a scale that fills about 75% of the plotting area.

  • Include points, a best-fit line if required, and maintain space for readability.

  • For two dependent variables against the same independent variable, use two Y-axes (clearly labeled).

• Graphs rubric (4 marks): axis labels and units; suitable linear scale; correctly plotted points; appropriate line occupying ~75% of space.

Line graphs and relationships

• Line graphs show relationship between two continuous variables (e.g., temperature, time, depth, salinity) for one or more groups.

• Points joined by straight lines with a ruler; best-fit line may be curved if appropriate.

• Two dependent variables against the same independent variable may require two Y-axes.

• DRY MIX concept for graphs:

  • Dependent variable = Y-axis (Responding variable)

  • Independent variable = X-axis (Manipulated variable)

Presentation of data: examples and practice

• Practice tasks include graphing data (e.g., pH vs tadpoles) and identifying missing elements in graphs.

Histograms vs bar charts

• Histograms: frequency data (counts); independent variable on X; dependent (frequency) on Y; bars are connected (no gaps).

• Bar charts: show relationship between two variables when one is discrete; gaps between bars indicate discontinuity.