Experimental Design Chemistry Tutorial
- An experiment is conducted to test an hypothesis.
- An experiment that is well designed has these features:
⚛ A well defined aim (goal or objective).
⚛ Results that can be reproduced (precision).
⚛ Errors that can be analysed.
- A well-defined objective is an hypothesis that can be disproved by experiment.
- Results will most likely to be reproducible if
(a) the independent and dependent variables are well chosen
(b) all other variables are held constant
(c) you repeat the same experiment a number of times until the results agree
- Understanding the sources of error in an experiment BEFORE you conduct it can help you to
(a) minimise the error inherent in the experiment
(b) choose the most appropriate apparatus with which to conduct the experiment
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Defining the Aim of the Experiment
The aim, goal or objective, of an experiment is to test the validity of an hypothesis.
An hypothesis is a possible answer to a scientific question.
So, an experiment is conducted to decide whether the possible answer to the question is most likely to be "true" or not.
In science, it is very difficult, almost impossible, to "prove" an hypothesis, that is, it is almost impossible to say that the answer to the question is "true".
| Scientific Question:
|| What temperature does water boil at?
| Possible Answer:
|| Water boils at 100°C
If you issued a thousand city-dwellers all over the world with digital thermometers that read to the nearest 10°C, then they would all report back that water boils at 100°C.
But, will you have proved that the hypothesis is correct?
No. The best you could say is that the results of this experiment support the hypothesis.
If you preformed the same experiment using digital thermometers that read to the nearest 0.1°C you would find a huge range of temperatures reported for the boiling point of water.
Have you disproved the hypothesis?
Yes. The results of this experiment disprove the hypothesis.
An hypothesis is useful when it is a statement that can be disproved(1).
Results of an experiment may support the hypothesis, but can rarely definitively prove the hypothesis to be true.
Results of an experiment that do not support the hypothesis can be said to disprove the hypothesis.
A well-defined aim, goal or objective, will be one which can be tested experimentally and can be disproved.
Designing an Experiment so that Results are Reproducible
It is important to design an experiment so that the same results are acheived every time you, or someone else, performs the experiment.(2)
When you can do the experiment many times and achieve the same results we say that the results of the experiment are reproducible.
This means you are going to have to design an experiment so that:
- you can control the all the possible variables
- the results are reliable (can be reproduced)
The first step in ensuring that the results of your experiment can be reproduced is to reduce the number of factors that can change during the experiment.
The different factors, or quantities, that can change are known as variables.
Before you even begin to think about how you will conduct the experiment, you will need to make a list of all the variables that you can think of that could affect the results of the experiment.
This is really hard to do without prejudice!
You can NOT afford to make any value judgements about the "quality" of the variables at this stage, you need to list all the things that could change, even if you think it is unlikely or a bit silly.
Example: What are the possible variables (quantities that could change) in an experiment to find the boiling point of water?
- Is all "water" the same? What about "hard water" and "soft water"? "Mineral water" and "spring water"? "Distilled water" and "tap water"? "Fresh water" and "seawater"? etc, etc, So, "water" is a variable!
- How much water will be boiled? 1 litre? 500 mL ? 10 mL ? So, volume of water is a variable.
- How will you measure the volume of water used? Kitchen measuring cup? 100 mL measuring cylinder? 500 mL volumetric flask? 25 mL transfer pipette? Apparatus used to measure volume is a variable.
- What sort of container will be used to hold the water while it boils? Aluminium saucepan? Stainless steel pot? Glass beaker? etc So, the type of container is a variable.
- What about the size of the container? Will you use a 50 mL beaker? 250 mL beaker? 1 L beaker? 2 L saucepan? 10 L pot? Size of container is a variable.
- What shape of container will you use? Tall, thin 100 mL beaker? Short, squat 100 mL beaker? Shape of container is a variable.
- What heat source will you use to heat the water to boil it? Bunsen burner? Stove top hotplate? Camp fire? Spirit burner? Heat source is a variable.
- How far from the heat source will you position your container of water? 1 cm? 50 cm? 1 m ? Distance from heat source is a variable.
- How will you keep the container in position while the water boils? Suspended above the heat source using string? Sitting on a tripod? Sitting directly on the hotplate? Method of suspension is a variable.
- What will you use to measure the temperature of the water? Mercury thermometer? Alcohol thermometer? Digital thermometer? Apparatus used to measure temperature is a variable.
- Where will you take the temperature of the water? On the bottom of the container? 1 mm from the bottom of the container? 1 cm from the bottom of the container? Where you take the water temperature is a variable.
- How will you suspend the thermometer in the water? Clamped to a retort stand? Suspended from a piece of strong? Resting on the bottom of the container? How you suspend the thermometer in the water is a variable.
- How long will you run the experiment for? 30 minutes? Until all the water has boiled off? Until half the water has boiled off? Duration of experiment is a variable.
- Where will you conduct the experiment? In your home kitchen? School's kitchen? School's laboratory? Where you conduct the experiment is a variable.
- What time will you conduct the experiment? Between 2pm and 5pm? Between 10 am and 11 am ? The time when you conduct the experiment is a variable.
- On which day will you conduct the experiment? The hottest day in summer? Coldest day in winter? Wettest day in Spring? Driest day in Autumn? Summer solstice? Halloween? The type of day you conduct the experiment is a variable.
Once you think you have listed all the possible variables, you need to make 2 very important decisions(3):
- Which of these variables will you change deliberately?
(called the independent variable)
- Which of these variables will you measure as it responds to the change you make?
(called the dependent variable)
Once you have made these decisions, you must then control ALL the other variables so that they do not change during the experiment. (called constant variables)
Example: We are testing the hypothesis that water boils at 100°C.
We could do this by measuring and recording the temperature of the water every 1 minute.
The variable we will change deliberately is time (the independent variable is time). That is, we will be taking measurements very minute.
The variable that will respond to this change is the temperature of the water (the dependent variable is temperature).
Every other variable must now be controlled to remain the same during the experiment (all other variables except time and temperature will be constant variables).
| Type of Variable
| Independent Variable
|| same stopwatch / graduated in seconds
| Dependent Variable
|| same alcohol thermometer / graduated in 1°C
| Constant Variables
|| Type of water
|| same water source for all experiments / distilled water
| Volume of water
|| same volume for all experiments / 50.00 mL
| Apparatus used to measure volume
|| same apparatus to measure all volumes / 50.00 mL transfer pipette
| Type of container
|| same container used for all experiments / pyrex beaker
| Size of the container
|| same beaker used for all experiments / 250 mL beaker
| Shape of container
|| same beaker used for all experiments / 250 mL beaker
| Heat source
|| same heat source for all experiments / blue flame of bunsen burner
| Distance from the heat source
|| same distance from heat source for all experiments / (use tripod with gauze mat)
| Apparatus to keep the container in position
|| same apparatus for all experiments / same tripod and gauze mat
| Where you take the water temperature
|| same position / 1 cm from bottom of beaker
| Suspending thermometer in water
|| same apparatus used for all experiments / clamp from retort stand
| Duration of experiment
|| continue for same length of time / 10 minutes
| Where you conduct the experiment
|| same place for all experiments / school laboratory
| Time you conduct the experiment
|| same time for all experiments / same classroom period
| Type of day
|| same day for all experiments / same period on same day in same lab
Where you conduct the experiment, the time, the type of day etc, are important, they lay the foundations for the conditions under which the experiment is conducted.
Where you conduct your experiment can then be thought of as the height above sea level condition.
The time/type of day can be thought of the temperature condition, the humidity condition, and the atmospheric pressure condition.
Reliability of the Results of your Experiment
How will you know if the results of your experiment are reliable?
There really is only one way to determine how reliable your results are.
You will need to repeat the experiment several times and see if the results for each experiment agree with each other.(4)
How many times should you repeat your experiment?
A general rule of thumb for High School Chemistry students is to do one quick experiment to determine the approximate result of the experiment, then perform as many careful experiments as is required to get 3 results within 2% agreement.(5)
These are known as concordant results.
Estimating Errors in your Experiment
Before you begin an experiment, you should be aware of the types of errors that are possible so that you can reduce their impact on your results.
There are two types of errors;
- random errors
- systematic errors
You have no control over random errors such as fluctuations in the temperature of a bunsen burner flame caused by fluctuations in the gas supply to the burner for instance.
Repeating the experiment in order to get results in close agreement with each other should compensate for these random errors.
You do have some control over systematic errors, so you need to think about the types of errors that are inherent in the experiment you are designing.
In the boiling water example, we have decided to use the same amount of water for all the experiments.
The most common ways of measuring an "amount" of substance in Chemistry is to weigh out a mass of the substance or to measure out a volume of the substance.
If we use a constant volume of water, say 50 mL, there will be different systematic errors depending on the apparatus we use to measure out the volume:
- 50.00 mL transfer pipette might have a tolerance of ± 0.03 mL so with the bottom of the miniscus sitting on the mark of the pipette the volume could be as low as 50.00 - 0.03 = 49.07 mL or as high as 50.00 + 0.03 = 50.03 mL
- 50.00 mL burette might have a tolerance of ± 0.06 mL so with the bottom of the meniscus sitting on the 50.00 mL mark, the volume in the burette could be as low as 50.00 - 0.06 = 49.04 mL or as high as 50.00 + 0.06 = 50.06 mL
- If you used a measuring cylinder graduated in 1 mL divisions, you can only feel certain about the measurement to the nearest mL, but the amount of uncertainty in the measurement is half the limit of reading, that is half of 1 mL. So with the bottom of the meniscus sitting on the 50 mL mark, the volume could be as low as 49.5 mL or as high as 50.5 mL.
The transfer pipette would result in the smallest amount of systematic error, so it might be considered the best option for measuring out 50.00 mL of water.
But, the transfer pipette has been designed to deliver 50.00 ± 0.03 mL ONLY at 20°C.
Many substances, like water, expand as they get warmer, so the volume of water increases as it gets warmer.
If the temperature is not 20°C you would need to calibrate the transfer pipette in order to determine the volume of water being delivered at that temperature.
Instead of using 50.00 mL of water, we could instead use 50.00 g of water.
If we used an electronic balance that measures mass to the nearest 0.0001 g there is a large degree of uncertainty in the last decimal place.
Is the mass really 49.9999 but was rounded up to 50.0000 g?
Or was the mass 50.0001 g that was rounded down to 50.0000 g ?
We don't know, so we might say that the uncertainty in the measurement is ±0.0001 g.
Compared with the systematic error involved in measuring the volume of water, the systematic error in measuring the mass of water appears to be lower.
We might therefore decide to weigh out 50.0000 ±0.0001 g of water instead of measuring out a volume of 50.00 ±0.03 mL of water in order to reduce the systematic error.
Similarly, we would need to determine what sort of thermometer to use.
One graduated in 1°C?
One graduated in 0.1°C?
The limit of reading on a thermometer graduated in 1°C divisions is 0.5°C.
The limit of reading on a thermometer graduated in 0.1°C divisions is 0.05°C.
We might decide that it is important to have greater certainty in the temperature measurement and opt for the thermometer graduated in 0.1°C divisions in order to reduce systematic errors in the experiment.
Thinking about sources of error BEFORE you set up an experiment enables you to:
- reduce the systematic error in an experiment before it is conducted
- select the most appropriate apparatus with which to conduct the experiment
(1) This is referred to as the Principle of falsification.
(2) It is important that the results of the experiment do not depend on some special sensitivity of the experimenter, that is, other people must be able to perform the same experiment as you and get the same results.
When some special sensitivity of the experimenter is required in order to achieve reproducible results, this is referred to as the Hieronymus Effect.
The Hieronymus Effect is named after an early twentieth century engineer, Thomas Galen Hieronymus, who postulated that there was an unknown, non-electromagnetic radiation emitted by the sun (and by all matter) which he described as "eloptic energy".
He performed experiments using a device he constructed himself to detect this "eloptic energy" and the results of his experiments supported his hypothesis that this "eloptic energy" existed.
The Hieronymus Machine was patented in 1947 and was used to diagnose and treat medical conditions in crops and farm animals.
His field of science was given the name "psionics", while Hieronymus himself was awarded an honorary PhD in physics.
Unfortunately, when scientists tried to repeat his experiments under strictly controlled conditions they could not reproduce the results of his experiments.
"Eloptic energy", "psionic energy", was only detectable by Heironymus and a few other "wishful-thinking" people, but definitely not detectable by scientists.
(3) "One Variable At a Time" (OVAT) approach assumes the 2 variables are independent of each other.
(4) We do not propose to discuss the statistical significance of results here.
(5) We do not propose to discuss a statistical approach to error analysis here.