Unit 0 - Practical Skills
Experiment Planning
Independent Variable: The one thing you change on purpose (what you test).
Dependent Variable: What you measure or observe (the result of the change).
Controlled Variables: Everything else you keep the same to make the test fair.
Example (just so you understand):
Independent Variable: Amount of sunlight
Dependent Variable: Plant growth
Controlled Variables: Type of plant, soil, water, pot size, temperature
Lab Based Experiment
Number of Organisms to Use:
Microscopic organisms → 20,000 – 50,000
Small organisms (e.g., larvae) → 100 – 500 per group
Medium organisms (e.g., snails) → 50 – 100 per group
Large organisms (e.g., crabs) → 5 – 30 per group
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Duration of Experiment:
* Small organisms → 1 – 2 weeks (they reproduce quickly)
* Larger organisms → 2 – 4 weeks
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Repeats (Reliability & Validity):
* Repeat the experiment 3–5 times for each variable
* This improves validity and reliability
* Calculate a mean average from the raw data
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Safety & Ethical Considerations:
* Handle organisms carefully to avoid harm
* Minimize stress and disturbance to specimens
* Be cautious of hazards such as:
* Burns from hot lamps
* Electrical equipment near water
* Follow proper lab safety procedures at all times
3. Working Ethically & Safely
Hazard: Hot and glass equipment
Risk: Burns skin and enters eye/skin
Precaution: Take care/use tongs and wear goggles/pick up glass with tweezers
Working Ethically with Living Organisms
When working with living organisms, it is important to minimize harm and avoid affecting their survival or natural habitat.
* Removing organisms safely:
Organisms should be collected gently using appropriate tools (e.g., nets or forceps) to avoid injury. Only the minimum number needed should be taken, and they should be kept out of their natural environment for the shortest time possible.
* Marking/tagging organisms safely:
If organisms need to be marked, non-toxic and non-invasive methods should be used. Marking should not affect their movement, behavior, or ability to survive.
* Being careful with the environment:
Avoid damaging the habitat when collecting organisms (e.g., do not disturb plants, rocks, or sediment unnecessarily). Return everything to its original position after the investigation.
* General care:
Keep organisms in suitable conditions (correct temperature, oxygen, and moisture). After the experiment, organisms should be returned safely to their original habitat.
4. Variables & Methods for Accurate Measurements
To measure:
Use: (for greater accuracy)
Temperature
digital thermometers
pH (%hydrogen ion)
pH probe, universal indicator(strips), litmus indicator(liquid)
Light intensity
approximated-using distance from light source
Volume
Measuring(graduated) cylinder, pipette
Mass
balance
Time
Stopwatch (cell phones ok)
Distance
ruler in mm or cm./tape measure in meters
Salinity
refractometer
5. Table - Predictions - Biological Drawings
-Use a single table per experiment
* Drawn before the exp. begins
* Large enough for data & results + mean
* Ruled lines
* Border around it
* Independent variable - first column in table -X axis - include units (heading only)
* Dependent variable - Y axis - include units (heading)
-Sketch a graph to predict results - use a ruler - label X & Y axis
-Biological drawings must be made: (unit 4)
* Large & drawn in pencil - use ¾ of space
* Bold, single, unbroken line
* Enough detail
* No shading whatsoever
* To make “Label lines”:
* always use a ruler
* line in pencil
* the label itself in pen
6. Presenting data in the form of graphs
Choosing the Correct Graph
* Continuous data (e.g., time, temperature: 1, 2, 3, 4…) → Line Graph
* Discontinuous/categorical data (e.g., species of coral) → Bar Chart
* Frequency data (e.g., number of fish feeding at different times) → Histogram
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General Graph Rules
* Always draw using a pencil and ruler
* Always start by labeling both axes with description + units
* Labels and units come directly from the results table
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Axes Guidelines
Independent Variable (IV):
* The variable you change
* Usually found in the first column of the table
* Plotted on the X-axis (horizontal)
* Scale should be evenly spaced and sensible
Dependent Variable (DV):
* The variable you measure (results)
* Plotted on the Y-axis (vertical)
* Scale should:
* Use at least ¾ of the graph area
* Be clear and evenly spaced
* Does NOT have to start at 0
7. Graph Drawing
8. For a line graph:
1. plot each point using a small x (no blobs!!!)
2. Join points with a ruler
9. For a bar chart or histogram - draw bars using a ruler
1. Bar chart - gaps between bars
2. Histogram - no gaps between bars (checking frequency)
10. Line of best fit - draw a line down an imaginary center with the same number of points on either side of the line
11. Write a key If there is more than one line on your graph = or label each line to make it clear which is which
Sources of errors/Anomalous results/Analysis of results
Analyzing Results (Patterns & Trends)
* Look for patterns or trends in the data (e.g., increase, decrease, no change)
* Identify any anomalous results (results that do not fit the pattern)
* Remember: Anomalies are only identified in raw data, not on graphs
* Suggest reasons for anomalies (e.g., human error, equipment error, uncontrolled variables)
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How to Answer “Describe & Explain” Questions
Usually aim for 3 strong points:
1. General trend:
* Overall pattern (e.g., “As temperature increases, the rate increases”)
2. Specific detail:
* Use actual data/values from the table (e.g., “From 10°C to 20°C, the rate increased from 5 to 12 units”)
3. Manipulate data (math):
* Show a calculation (e.g., increase of 7 units, or doubling)
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Control Variables Check
* Check if controlled variables stayed constant
* Ask: How much did they vary?
* If there is an anomaly, consider:
* Could changes in control variables have caused it?
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Suggesting Improvements
Aim to improve accuracy, reliability, and precision:
* Repeat trials (more data = more reliable)
* Use more precise equipment (improves accuracy)
* Control variables more carefully
* Increase sample size
* Test in different locations/conditions (for broader validity)
Evaluation/Analysis/Conclusions
Evaluate Procedure & Data
* Decide how confident you are in your conclusions based on your data* Identify limitations of your procedure (e.g., equipment accuracy, sample size, time constraints)* Identify sources of error (e.g., human error, measurement errors, environmental factors) * Suggest improvements to make the experiment more accurate, reliable, or valid
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Analyze Data & Identify Trends
* Describe patterns or trends in the results (e.g., “As X increases, Y decreases”)* Describe the relationship between the independent and dependent variables* Highlight any anomalous results and suggest possible explanations * Use scientific knowledge to explain why these trends occur
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Link Back to Hypothesis
* State whether your results support or refute the hypothesis* Justify your conclusion using evidence from your data
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Suggest Further Investigations
* Propose new questions that could be investigated (e.g., testing different conditions, species, or time periods)* Make predictions for these investigations based on your results
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Example Structure for Writing:
1. Trend: “The growth of snails increased as water temperature increased from 15°C to 25°C.”
2. Scientific Explanation: “This is because higher temperatures increase metabolic rate, leading to faster growth.”
3. Evaluation: “The conclusion is reliable because we repeated the experiment 5 times, but a limitation is the small sample size of snails.”
4. Improvements: “Use larger sample sizes and more temperature intervals to increase accuracy.”
5. Further Questions & Predictions: “Would growth continue to increase above 25°C? It is predicted that growth would decline above the optimal temperature.”