Welcome to the Lab Evaluation Guide!

In Chemistry, performing an experiment is only half the battle. The real "science" happens when you look at your results and ask: "How do I know this is right?" and "How could I make it better next time?" In your Unit 3 exam, you aren't just tested on what you did, but on your ability to be a "science detective" who critiques the methods used.

In this chapter, we will learn how to spot errors, calculate how "off" our measurements might be, and suggest clever ways to improve our experiments.

When you evaluate a method, you are looking for things that might have made the results less accurate. Don't worry if this feels like "finding faults"—that is exactly what a good chemist does!

Common Methodological Issues

  • Heat Loss: In thermochemistry experiments (like CP2), heat escaping to the surroundings is the most common error. This leads to a lower temperature change (\( \Delta T \)) than expected.
  • Incomplete Reactions: Sometimes the chemicals don't react fully, which means your yield or gas volume will be lower than the theoretical value.
  • Side Reactions: Other reactions might be happening at the same time, using up your reactants.
  • Gas Escaping: In experiments measuring gas volume (like CP1), gas might leak out before you can pop the bung on the flask.
  • Measurement Resolution: Using a piece of equipment that isn't precise enough (e.g., using a \( 100 \text{ cm}^3 \) measuring cylinder to measure \( 5 \text{ cm}^3 \) of liquid).

Quick Tip: If an exam question asks you to evaluate a method, look at the specific Core Practical it refers to. For example, if it's about CP1 (Molar Volume of Gas), think about gas escaping or the gas being soluble in water!

2. Understanding Errors: Random vs. Systematic

To evaluate a conclusion, you need to know why your result is different from the "true" value. We categorize these differences into two types of errors:

Random Errors

These cause results to fluctuate around the true value. They are unpredictable and vary each time you repeat the experiment.

  • Example: Human reaction time when stopping a stopwatch or difficulty deciding exactly when a color change happens in a titration.
  • The Fix: Repeat the experiment multiple times and calculate a mean (average). This cancels out the "highs" and "lows."

Systematic Errors

These are "built-in" flaws that shift every single result in the same direction (always too high or always too low).

  • Example: A thermometer that always reads \( 1^{\circ}\text{C} \) too high, or heat loss in a calorimeter.
  • The Fix: You cannot fix this by repeating the experiment. You must change the method or recalibrate the equipment.

3. Measurement Uncertainty and Accuracy

Every piece of lab equipment has an uncertainty. This is the "plus or minus" range of the measurement. To evaluate how much this affects your conclusion, we calculate the percentage uncertainty.

The formula you need to know is:

\( \text{Percentage Uncertainty} = \frac{\text{Uncertainty}}{\text{Reading}} \times 100\% \)

Wait! What if I take two readings?

If you are calculating a change (like a temperature change \( \Delta T \) or a burette titre), you have used the equipment twice. Therefore, you must double the uncertainty.

\( \text{Percentage Uncertainty (for a change)} = \frac{2 \times \text{Uncertainty}}{\text{Measured Value}} \times 100\% \)

Example: If a burette has an uncertainty of \( \pm 0.05 \text{ cm}^3 \) and your titre is \( 25.00 \text{ cm}^3 \):
\( \frac{2 \times 0.05}{25.00} \times 100\% = 0.4\% \)

4. Evaluating Conclusions: Comparing to Data

Once you have your result, you need to draw a conclusion. But is it a good conclusion? Here are the three pillars of evaluation:

  • Accuracy: How close is your experimental value to the actual "literature" value? We often calculate Percentage Error to see this:
    \( \frac{\text{Experimental Value} - \text{True Value}}{\text{True Value}} \times 100\% \)
  • Precision: How close are your repeated results to each other? If they are all very close, your technique is precise.
  • Validity: Does the experiment actually test what it was supposed to? If you forgot to control a variable (like pressure in a gas experiment), your conclusion might not be valid.

Did you know? An anomaly (or outlier) is a piece of data that doesn't fit the trend. When evaluating conclusions, you should identify anomalies and explain why they might have happened (e.g., "The reaction was started before the bung was secure"). Never include anomalies in your average!

5. Suggesting Improvements

This is the "Level 3" skill in Unit 3. You need to provide specific, practical solutions to the problems you identified in the method.

Problem: Heat loss to surroundings.
Improvement: Use a polystyrene cup as a calorimeter (better insulator), add a lid, or use cooling curve corrections (plotting a graph of temperature against time and extrapolating back to the time of mixing).

Problem: Uncertainties are too high.
Improvement: Use a larger mass/volume of reactants to create a larger reading (which decreases the percentage uncertainty) or use more precise equipment (e.g., a volumetric pipette instead of a measuring cylinder).

Problem: Gas loss in a reaction.
Improvement: Use a sealed system or place the solid reactant in a small sample tube inside the flask, then tip the flask to start the reaction without opening the bung.

Problem: Incomplete combustion.
Improvement: Increase the oxygen supply (e.g., using a bomb calorimeter). (Note: This relates to Topic 6: Energetics).

Summary: The Evaluation Checklist

When you are faced with an evaluation question in the exam, run through this mental checklist:

  1. Identify the error: Is it heat loss? Gas escaping? Measurement uncertainty?
  2. Categorize it: Is it a random error or a systematic error?
  3. Quantify it: Calculate the percentage uncertainty if you have the numbers.
  4. Compare it: Is the percentage error between your result and the true value larger than the equipment's percentage uncertainty? If yes, then there must be methodological errors (like heat loss) beyond just equipment limits.
  5. Fix it: Suggest a specific piece of equipment or a change in the procedure to make it better.

For more details on specific equipment used in these evaluations, see the chapter on "Apparatus, Techniques and Laboratory Safety". For details on calculating yields to evaluate efficiency, see "Topic 1: Formulae, Equations and Amount of Substance".