A control experiment is a comparative experiment conducted to determine whether a change observed in an experiment was truly caused by the factor being investigated.
In chemistry experiments, the effects of experimental conditions are clarified by comparing cases with and without the addition of a reagent, with and without a catalyst, with and without light irradiation, with and without heating, with and without a sample, or before and after treatment.
Properly setting up a control experiment greatly increases the persuasiveness of the experimental results.
In discussing a control experiment, it is not sufficient to write only that “a change occurred compared with the control.”
It is necessary to explain what was compared, which conditions were kept the same, which condition alone was changed, and what the difference between the control group and experimental group means.
It is also important to discuss the reason when no difference is observed.
A control experiment forms the basis that supports the conclusion.
This article clearly explains, as examples of discussions that can be used in laboratory reports on control experiments, the control group, experimental group, comparison conditions, positive control, negative control, blank, standardization of operating conditions, discussion when a difference is observed or not observed, how to write the conclusion, causes of error, and points for improvement.
Note:
This article is a reference intended to assist with discussions of control experiments conducted in basic chemistry experiments, analytical chemistry experiments, organic chemistry experiments, inorganic chemistry experiments, biochemistry experiments, and materials chemistry experiments at universities and similar institutions.
For the actual setup of control groups, comparison methods, statistical processing, and how to write conclusions, always follow the instructions in your university’s laboratory manual and those given by your instructor or TA.
- What Is a Control Experiment?
- Main Items to Include in the Results
- Difference Between the Control Group and Experimental Group
- Meaning of Keeping Comparison Conditions Consistent
- What Is a Positive Control?
- What Is a Negative Control?
- Difference Between a Blank and a Control Experiment
- Discussion When a Difference Is Observed in a Control Experiment
- Discussion When No Difference Is Observed in a Control Experiment
- Relationship Between Control Experiments and Conclusions
- Problems When the Comparison Target Is Inappropriate
- Importance of Keeping the Sample Amount the Same
- Importance of Keeping Temperature and Time the Same
- Importance of Keeping Concentration and pH the Same
- Control Experiments and Reproducibility
- When the Difference in Measured Values Is Within the Error Range
- Control Experiments and Causality
- Causes of Error in Control Experiments
- When the Results Can Be Considered Good
- Example Discussions When the Experiment Did Not Go Well
- How to Write Points for Improvement
- How to Write the Conclusion
- Difference Between a Superficial Discussion and a Good Discussion
- Examples of Expressions That Can Be Used in Reports
- Points to Check When Discussing Control Experiments
- Summary
What Is a Control Experiment?
A control experiment is an experiment in which conditions other than the one being investigated are kept as similar as possible, and only a specific condition is changed so that the results can be compared.
For example, when investigating the effect of a catalyst, an experiment with the catalyst is compared with an experiment without the catalyst.
In this case, the amounts of reactants, solvent, temperature, reaction time, stirring conditions, and other factors are kept as similar as possible.
Conducting a control experiment makes it easier to determine whether an observed change was caused by the factor being investigated or by another factor.
In an experiment without a control, even if a result is obtained, it becomes difficult to explain whether the result was truly caused by differences in operating conditions.
Therefore, control experiments are important for increasing the reliability of conclusions.
Example Discussion:
A control experiment is conducted by keeping conditions other than the factor being investigated the same and confirming how the result changes depending on the presence, absence, or difference of that factor.
In this experiment, by comparing the control group and experimental group, it is possible to determine whether the observed change originated from the treatment condition.
Therefore, a control experiment is an important comparison condition that supports the interpretation of results and the validity of conclusions.
Main Items to Include in the Results
In the results of a control experiment, it is important to clearly describe the conditions of the control group and experimental group.
Organize which conditions were kept the same, which condition alone was changed, and what kind of difference appeared in the results.
Not only cases in which a difference was observed, but also cases in which no difference was observed are important results.
Main Items to Include in the Results
- Conditions of the control group
- Conditions of the experimental group
- Factor that was changed
- Conditions that were kept the same
- Measurement items
- Measured values
- Mean
- Standard deviation
- Difference from the control group
- Direction of the difference
- Magnitude of the difference
- Presence or absence of change
- Presence or absence of positive and negative controls
- Presence or absence of blank correction
- Causes of error
- Conclusion
- Points for improvement
Example of How to Write the Results:
While almost no progress of the reaction was observed in the control group, a clear color change and an increase in the measured value were confirmed in the experimental group.
The amount of reagent, temperature, and reaction time were kept the same in both groups, and only the treatment condition was changed.
Therefore, the observed difference was considered likely to have been caused by the difference in treatment conditions.
Difference Between the Control Group and Experimental Group
The control group is the condition used as the basis for comparison.
The experimental group, on the other hand, is the condition in which the factor being investigated is added or changed.
Rather than looking only at the results of the experimental group, the effect of the factor being investigated is determined by comparison with the control group.
For example, when investigating whether a certain reagent causes precipitation, an experimental group in which the reagent is added is compared with a control group in which the reagent is not added.
If precipitation occurs only in the experimental group and not in the control group, the reagent can be considered to have been involved in the formation of the precipitate.
However, if the other conditions are not the same, the comparison will not be valid.
| Item | Meaning | Point for Discussion |
|---|---|---|
| Control group | Condition used as the basis for comparison | Confirm whether the change occurs naturally |
| Experimental group | Condition in which the factor being investigated is added | Determine the effect of the factor from the difference from the control group |
Example Discussion:
The control group is the condition used as the basis for comparison, while the experimental group is the condition in which the treatment being investigated is added.
If a change is observed only in the experimental group, the change is likely to have originated from the treatment condition.
However, if conditions other than the treatment condition differ between the control group and experimental group, the cause of the difference cannot be narrowed down to a single factor, so it is important to keep the comparison conditions consistent.
Meaning of Keeping Comparison Conditions Consistent
The most important point in a control experiment is to keep conditions other than the one being investigated as similar as possible.
For example, if temperature, reaction time, amount of reagent, amount of solvent, pH, stirring conditions, duration of light irradiation, sample amount, or other conditions differ, it becomes impossible to determine which condition caused the difference in the results.
By keeping the conditions consistent, the difference between the control group and experimental group can be limited to the factor being investigated.
This makes it easier to explain the difference in the results as an effect of that factor.
If the conditions are not consistent, avoid making a definitive conclusion and discuss the possibility that multiple factors affected the results.
Example Discussion:
In the control group and experimental group, the reaction temperature, reaction time, amount of reagent, and amount of solvent other than the condition being investigated were kept the same.
This makes it possible to discuss the difference in the results mainly as being caused by the difference in treatment conditions.
If the conditions are not kept consistent, it becomes impossible to determine which factor caused the observed difference, so standardizing the comparison conditions is important in control experiments.
What Is a Positive Control?
A positive control is a condition in which a reaction or change is already known to occur.
It is used to confirm that the experimental system is functioning correctly.
For example, in an experiment that confirms a color reaction, using a standard substance known to produce the color makes it possible to confirm whether the reagents and measurement method are functioning normally.
If the expected reaction does not occur in the positive control, even if no change is observed in the experimental group, it cannot be concluded that the sample has no effect.
There may be a problem with the experimental system itself, such as deterioration of the reagents, inadequate measurement conditions, or insufficient reaction time.
A positive control is important for confirming that the experiment itself is functioning properly.
Example Discussion:
Because the expected reaction was confirmed in the positive control, the reagents and measurement method used in this experiment were considered to have functioned normally.
Therefore, the change observed in the experimental group was likely to have originated from the sample or treatment condition rather than from a malfunction of the measurement system.
On the other hand, if no reaction is observed in the positive control, a problem with the experimental system itself must first be suspected.
What Is a Negative Control?
A negative control is a condition in which no reaction or change is expected to occur.
It is used to confirm background reactions, natural changes, or changes caused by factors other than the reagent.
For example, a condition in which no reagent is added or a condition using a nonreactive substance can serve as a negative control.
If a change occurs in the negative control, the change observed in the experimental group can no longer be attributed only to the factor being investigated.
It is necessary to consider reagent contamination, effects of the solvent, contamination of equipment, natural decomposition, or the effects of light or temperature.
A negative control is important for confirming background changes.
Example Discussion:
Because almost no change was observed in the negative control, the reaction in this experiment was considered unlikely to proceed through the effects of the reagent, solvent, or operating conditions alone.
On the other hand, a clear change was observed in the experimental group, so the difference was likely to have been caused by the treatment condition.
If a change had also been observed in the negative control, the effects of background reactions or contamination would need to be considered.
Difference Between a Blank and a Control Experiment
A blank is a condition used to correct for background values other than those originating from the sample.
For example, reagents or solvent alone are measured without the sample, and signals originating from the instrument or reagents are subtracted.
A control experiment, on the other hand, is a condition used to compare and evaluate the effect of a specific condition.
Both are important for comparison, but their purposes are slightly different.
A blank is mainly used to correct measured values, while a control experiment is used to determine the effect of experimental conditions.
For example, in absorbance measurement, absorption by the solvent and reagents is corrected using a blank, and the absorbance values of the control group and experimental group are compared to evaluate the treatment effect.
In a report, it is important not to confuse a blank with a control.
| Item | Main Purpose | Use |
|---|---|---|
| Blank | Correction of background values | Subtract from the measured value |
| Control experiment | Confirmation of the effect of a condition | Compare with the experimental group |
Example Discussion:
A blank is used to correct background values originating from reagents, solvents, or instruments, while a control experiment is used to determine the effect of treatment conditions.
Both are important for comparison, but there is a difference in purpose: the blank is used for correction, while the control is used for comparing conditions.
Therefore, when discussing experimental results, it is desirable to compare the control group and experimental group using values obtained after blank correction.
Discussion When a Difference Is Observed in a Control Experiment
If a clear difference is observed between the control group and experimental group, the condition being investigated may have affected the result.
However, rather than immediately concluding the cause simply because a difference was observed, check whether the other conditions were consistent, whether the difference exceeded the range of measurement error, and whether the result was reproducible.
If the difference is large, the same trend is observed in repeated measurements, and conditions other than the one being investigated are consistent between the control group and experimental group, it becomes easier to discuss the difference as being caused by the factor being investigated.
In the conclusion, show the direction and magnitude of the difference as evidence.
Example Discussion:
While the change was small in the control group, the measured value increased greatly in the experimental group.
Because the temperature, time, and amount of reagent other than the treatment condition were kept the same in both groups, this difference was considered to have been caused by the treatment condition.
Therefore, the treatment used in this experiment can be judged to have contributed to the progress of the target reaction or to an increase in the measurement signal.
Discussion When No Difference Is Observed in a Control Experiment
If no difference is observed between the control group and experimental group, the condition being investigated may not have had a large effect on the result.
However, caution is necessary before immediately concluding that there was no effect.
Possible reasons include treatment conditions that were too weak, a reaction time that was too short, insufficient measurement sensitivity, a low sample concentration, or too small a difference between the control conditions.
When no difference is observed, check whether the experimental conditions were set appropriately to detect an effect.
If a positive control is included and the expected change occurs in the positive control, it becomes easier to judge that the measurement system was functioning.
Conversely, if no change occurs even in the positive control, there may be a problem with the experimental system itself.
Example Discussion:
Because no large difference was observed between the control group and experimental group, the effect of the treatment under the conditions used in this experiment was considered small.
However, if the treatment time or concentration was insufficient, an actual effect may not have appeared in the measured values.
Therefore, to interpret a result in which no difference was observed, it is necessary to consider measurement sensitivity, treatment conditions, and the results of the positive control together.
Relationship Between Control Experiments and Conclusions
A control experiment provides evidence supporting the conclusion of a report.
From the results of the experimental group alone, it is impossible to determine whether the observed change was caused by the treatment, occurred naturally, or was caused by reagents or operations.
Comparison with the control group makes it possible to narrow down the cause of the change.
When writing a conclusion, use the difference between the control group and experimental group as evidence.
Rather than writing only that “the value increased in the experimental group,” writing that “the value did not increase in the control group but increased in the experimental group” makes the conclusion more persuasive.
It is important to limit the conclusion to what can be stated from the comparison results.
Example of How to Write a Conclusion:
While no large change in the measured value was observed in the control group, the measured value clearly increased in the experimental group.
This difference was considered to have been caused by the treatment condition that differed between the two groups.
Therefore, under the experimental conditions used in this study, it can be concluded that this treatment promoted the change in the measurement target.
Problems When the Comparison Target Is Inappropriate
In a control experiment, a correct conclusion cannot be reached if the comparison target is inappropriate.
For example, if the sample amount, temperature, reaction time, pH, or solvent amount differs between the experimental group and control group, it becomes impossible to determine which condition caused the difference in the results.
The control group must be made as similar as possible to the experimental group, except that the factor being investigated is omitted.
If an inappropriate control is used, the meaning of any observed difference becomes ambiguous.
In such a case, it is more appropriate to avoid making a definitive statement in the conclusion and instead write that “differences in multiple conditions may have affected the results.”
The validity of the control conditions is directly related to the reliability of the experimental results.
Example Discussion:
If the reaction time or temperature differed between the control group and experimental group, it would be impossible to determine whether the observed difference was caused by the treatment condition or by differences in temperature or time.
With this type of comparison, it is difficult to clearly conclude that there was a treatment effect.
Therefore, in a control experiment, conditions other than the factor being investigated must be kept as consistent as possible.
Importance of Keeping the Sample Amount the Same
If the sample amount differs between the control group and experimental group, the difference in measured values may be caused by the difference in sample amount rather than by the treatment condition.
For example, absorbance, amount of precipitate, amount of gas generated, and titration volume may change in proportion to the sample amount.
Even if the value is larger in an experimental group with a larger sample amount, this does not necessarily indicate a treatment effect.
In a control experiment, the sample amount should be kept the same, or, when necessary, values should be converted to values per unit mass, per unit volume, or per unit concentration for comparison.
It is important not to compare raw measured values alone, but to evaluate them as values obtained under consistent conditions.
Example Discussion:
If the sample amount differs between the control group and experimental group, the difference in measured values may be caused by the difference in sample amount rather than by the treatment condition.
Therefore, it is necessary to use the same sample amount or convert the results to values per unit amount for comparison.
In this experiment, because the sample amount was kept the same, the difference in measured values could be more easily discussed as an effect of the treatment condition.
Importance of Keeping Temperature and Time the Same
In chemical reactions, temperature and time greatly affect the results.
If the temperature or reaction time differs between the control group and experimental group, the reaction rate or amount of product changes, making it impossible to correctly compare the effect of the treatment condition.
Standardizing temperature and time is particularly important in reaction-rate experiments, color reactions, enzyme reactions, adsorption experiments, and decomposition reactions.
If temperature and time are kept consistent, the effect caused by the difference in treatment conditions can be determined more clearly.
If there was a difference in temperature or time, the possibility that this difference affected the results should be included in the discussion.
In a report, it is important to clearly state the conditions necessary for comparison.
Example Discussion:
By keeping the reaction time and temperature the same in the control group and experimental group, the difference between the two could be discussed as being caused by the difference in treatment conditions.
If the temperature had differed, differences in reaction rate could have affected the measured values and made it impossible to accurately determine the treatment effect.
Therefore, keeping temperature and time consistent is important in control experiments.
Importance of Keeping Concentration and pH the Same
Reactant concentration and pH affect the progress of chemical reactions, color development, precipitation, adsorption, enzyme activity, and other processes.
If concentration or pH differs between the control group and experimental group, the difference in the results may have been caused by the difference in concentration or pH rather than by the condition being investigated.
The effect of pH is particularly large in acid-base reactions and metal-ion reactions.
In a control experiment, the concentration and pH should be kept the same, or if they are intentionally changed, the reason should be made clear.
Measures such as using a pH buffer, keeping reagent concentrations the same, and keeping the total solution volume the same are necessary.
If the conditions are not consistent, the reliability of the conclusion decreases.
Example Discussion:
By keeping the pH the same in the control group and experimental group, it became easier to discuss the observed change as being caused by the difference in treatment conditions.
If the pH differed, the ionization state of the reactants, formation of precipitates, or progress of the color reaction could have changed.
Therefore, in experiments affected by pH, it is important to keep the pH of the control group and experimental group the same.
Control Experiments and Reproducibility
In a control experiment, a single comparison may not be sufficient to ensure the reliability of the results.
It is important to perform multiple measurements under the same conditions and confirm whether the difference between the control group and experimental group is reproduced.
If the result is reproducible, the observed difference is more likely to have been caused by the difference in conditions rather than by chance.
Conversely, if the results vary greatly between measurements, it becomes difficult to determine whether the difference between the control group and experimental group is truly meaningful.
Using the mean, standard deviation, error bars, and similar measures makes it easier to evaluate the reliability of the difference.
In control experiments, reproducibility is important in addition to the presence or absence of a difference.
Example Discussion:
Because the difference between the control group and experimental group showed the same trend in multiple measurements, this difference was considered to have been caused by the treatment condition rather than by chance.
On the other hand, if the measured values vary greatly, uncertainty remains in the conclusion even if there is a difference in the mean.
Therefore, in a control experiment, it is important to confirm not only the mean but also the standard deviation and reproducibility.
When the Difference in Measured Values Is Within the Error Range
Even if there is a difference between the mean values of the control group and experimental group, it is difficult to say that there is a clear difference if the difference falls within the variation or error range of the measured values.
If the standard deviation or error bars are large, the apparent difference may be caused by random error.
In this case, definitive statements should be avoided in the conclusion.
If the difference in measured values is within the error range, it should be expressed as “no clear difference was confirmed under the measurement conditions used in this experiment.”
Increasing the number of measurements, improving measurement precision, or increasing the difference between conditions may make it possible to evaluate the difference more clearly.
Example Discussion:
A difference was observed between the mean values of the control group and experimental group, but when the standard deviation was taken into account, the difference was within the range of variation in the measured values.
Therefore, it cannot be concluded from the results of this experiment alone that the treatment condition had a clear effect.
To make a more reliable judgment, it is necessary to increase the number of measurements, improve measurement precision, and compare the groups again.
Control Experiments and Causality
Control experiments are important when considering causal relationships.
If a change is observed in the experimental group but not in the control group, the change is more likely to be related to the condition added to the experimental group.
However, to strongly claim a causal relationship, the comparison conditions must be appropriate, the result must be reproducible, and other factors must have been excluded.
If the conditions are not sufficiently consistent or the number of measurements is small, it is more appropriate to use expressions such as “may have affected.”
In chemistry laboratory reports, it is important not to make conclusions beyond what can be stated from the control experiment.
Conclusions should remain within the range supported by the data.
Example Discussion:
Because a clear change was observed only in the experimental group and the change was small in the control group, the condition added to the experimental group was likely to have affected the result.
However, to demonstrate a causal relationship more reliably, it is necessary for all other conditions to be completely consistent and for the same trend to be reproduced.
Therefore, in this experiment, the treatment condition was considered likely to have been involved in the observed change.
Causes of Error in Control Experiments
Causes of error in control experiments include inconsistencies in conditions between the control group and experimental group, differences in sample amount, differences in temperature or time, differences in pH or concentration, variation in measuring instruments, deterioration of reagents, differences in operating order, and sample inhomogeneity.
When these occur, the difference in results can no longer be explained solely by the factor being investigated.
In addition, if the control group and experimental group are measured on different days or using different instruments, differences in environmental conditions or instrument conditions may affect the results.
It is desirable to perform measurements at the same time, using the same instrument and the same operating procedure whenever possible.
In a control experiment, fairness of the comparison determines the reliability of the results.
Example Discussion:
Possible causes of error in the control experiment include the possibility that the temperature, reaction time, and sample amount were not completely identical between the control group and experimental group.
If these conditions differ, it becomes difficult to determine whether the difference in measured values was caused by the treatment condition being investigated.
Therefore, in a control experiment, it is important to keep variables other than the treatment condition as constant as possible.
When the Results Can Be Considered Good
Results of a control experiment can be considered good when the conditions of the control group and experimental group are appropriately matched and a clear difference caused by the condition being investigated is confirmed.
Furthermore, if the positive and negative controls produce the expected results and the measurements are reproducible, the reliability of the conclusion increases.
Even when no difference is observed, if appropriate controls and sufficient reproducibility are present, the result can lead to the meaningful conclusion that “no effect was confirmed under the conditions used in this experiment.”
A good control experiment is not one in which the expected result is obtained, but one in which conditions are established that allow a judgment to be made through comparison.
Example Discussion:
Conditions other than the treatment condition were consistent between the control group and experimental group, and a clear change was confirmed only in the experimental group.
In addition, the positive and negative controls produced the expected results, indicating that the experimental system was functioning appropriately.
Therefore, the effect of the treatment condition was considered to have been evaluated with relatively high reliability in this experiment.
Example Discussions When the Experiment Did Not Go Well
When a control experiment does not go well, consider the causes based on results such as a change occurring even in the control group, no change occurring in the positive control, a small difference between the control group and experimental group, large variation, or inconsistent conditions.
Organizing possible causes into control setup, measurement conditions, reagents, operating procedure, and reproducibility makes the discussion easier.
Example Discussion:
If a change was observed even in the negative control, a background reaction may have proceeded even without the addition of the sample.
In this case, the change observed in the experimental group cannot be concluded to have been caused only by the treatment condition.
Possible causes include reagent contamination, insufficient cleaning of equipment, and natural changes caused by temperature or light, so the control conditions must be reconsidered.
Another Example Discussion:
If the expected reaction was not confirmed in the positive control, the measurement system or reagents may not have been functioning normally.
Therefore, even if no change was observed in the experimental group, it cannot be concluded that the treatment had no effect.
It is necessary to check for reagent deterioration, insufficient reaction time, or inadequate measurement conditions and establish conditions under which the positive control reacts correctly.
Another Example Discussion:
A difference was observed between the mean values of the control group and experimental group, but the measured values showed large variation and the difference was within the error range.
In this case, it is difficult to conclude from the results of this experiment alone that there was a clear effect of the treatment condition.
Increasing the number of measurements and keeping the sample amount, reaction time, and measurement conditions consistent would make it possible to evaluate the presence or absence of a difference more accurately.
How to Write Points for Improvement
In a discussion of a control experiment, writing not only about problems with the comparison conditions and interpretation of the results but also about how the experimental conditions could be improved next time makes the report easier to organize.
Points for improvement can be organized into the setup of the control group, standardization of conditions, number of measurements, positive and negative controls, and data processing.
Improvements to Control Conditions
- Keep conditions other than the one being investigated consistent
- Use the same sample amount
- Keep the total solution volume the same
- Keep the reaction temperature constant
- Standardize the reaction time
- Keep pH and concentration consistent
- Measure using the same instrument and the same measurement conditions
- Keep the operating order consistent
Improvements to Increase the Reliability of the Conclusion
- Set up a positive control
- Set up a negative control
- Perform blank correction appropriately
- Increase the number of measurements
- Show the mean and standard deviation
- Check whether the difference is within the error range
- Measure the control group and experimental group at the same time
- Do not make conclusions beyond what can be stated from the results
Example of How to Write Points for Improvement:
To improve the reliability of the control experiment, the sample amount, temperature, reaction time, pH, and amount of reagent must be kept the same between the control group and experimental group, with only the condition being investigated changed.
In addition, setting up positive and negative controls makes it possible to confirm whether the experimental system is functioning correctly and whether background reactions are present.
Furthermore, increasing the number of measurements and showing the standard deviation makes it easier to determine whether the difference between the control group and experimental group is reproducible.
How to Write the Conclusion
In the conclusion of a control experiment, describe what can be stated from the comparison between the control group and experimental group.
The important point is not to make a conclusion beyond what can be stated from the data.
If there is a clear difference and the conditions are consistent, it can be written that the condition “is considered to have had an effect.”
If the difference is small or within the error range, it is more appropriate to write that “no clear effect was confirmed.”
Including the comparison target, direction of the difference, and meaning of the difference makes the conclusion easier to understand.
Rather than writing “it increased when A was performed,” writing something such as “the change was small in the control group but increased under condition A, suggesting that A may have promoted the reaction” produces a more logical conclusion.
Example Conclusion:
While no large change in the measured value was observed in the control group, the measured value increased in the experimental group.
Because conditions other than the treatment condition were kept consistent between the two groups, this increase was likely to have been caused by the treatment condition.
Therefore, under the experimental conditions used in this study, this treatment was considered to have promoted the change in the measurement target.
Example Conclusion When the Difference Is Small:
A slight difference was observed between the mean values of the control group and experimental group, but when the standard deviation was taken into account, the difference was within the range of variation in the measured values.
Therefore, no clear effect of the treatment was confirmed under the conditions used in this experiment.
A more reliable judgment would require increasing the number of measurements and conducting an experiment with the conditions standardized more strictly.
Difference Between a Superficial Discussion and a Good Discussion
In a discussion of a control experiment, simply writing “it was different from the control” or “there was a difference” results in a superficial discussion.
A good discussion explains what was compared, which conditions were kept the same, what the difference means, and how far a conclusion can be drawn.
| Superficial Discussion | Good Discussion |
|---|---|
| It increased compared with the control. | Because the change was small in the control group and the measured value increased only in the experimental group, the treatment added to the experimental group may have promoted the reaction. |
| No difference was observed. | Because no significant difference was observed between the control group and experimental group, no clear effect was confirmed under the treatment conditions used in this experiment, although insufficient treatment time or measurement sensitivity may also be possible causes. |
| A control experiment was performed. | By keeping temperature, time, and the amount of reagent other than the factor being investigated consistent and comparing the control group with the experimental group, the effect of the treatment condition was evaluated. |
| The control also reacted. | Because a change was also observed in the negative control, a background reaction or reagent contamination may have been present, making it difficult to explain the change in the experimental group solely by the treatment condition. |
| There was an effect. | Because the difference from the control group was reproduced and was sufficiently larger than the variation in the measured values, the treatment was considered likely to have had an effect under the conditions used in this experiment. |
Examples of Expressions That Can Be Used in Reports
The following expressions can be used when writing the results, discussion, and conclusion of a control experiment.
Adjust the necessary parts according to your own experimental results.
- A control experiment is conducted by keeping conditions other than the one being investigated consistent and comparing the effect of that condition.
- Because the change was small in the control group, the background reaction was considered small.
- Because a change was confirmed only in the experimental group, the treatment condition may have affected the result.
- Because the expected reaction was observed in the positive control, the experimental system was considered to have functioned normally.
- Because a change was observed in the negative control, the effects of background reactions or contamination must be considered.
- If conditions are not consistent between the control group and experimental group, it is difficult to explain the difference in results by a single factor alone.
- Because the difference in measured values was within the range of the standard deviation, it cannot be judged that there was a clear difference.
- Because the difference from the control group was reproduced, the effect of the treatment condition was considered relatively reliable.
- No clear effect was confirmed under the conditions used in this experiment.
- The conclusion must be limited to what can be stated from the comparison with the control group.
Points to Check When Discussing Control Experiments
Checking the following points before writing the report makes it easier to write the discussion.
- Are the control group and experimental group clearly distinguished?
- Is it stated what was compared?
- Is the condition that was changed clearly identified?
- Are the conditions that were kept the same explained?
- Is the meaning of positive and negative controls understood?
- Are blanks and controls not being confused?
- Has it been checked whether the difference in measured values is within the error range?
- Have the number of measurements and reproducibility been considered?
- Are the limitations described if the conditions were not consistent?
- Has the reason for the absence of a difference been considered?
- Is the conclusion limited to what can be stated from the data?
- Do the points for improvement correspond to the causes of error?
Summary
A control experiment is a comparative experiment conducted to determine whether a change observed in an experiment was truly caused by the factor being investigated.
The control group is the condition used as the basis for comparison, while the experimental group is the condition in which the factor being investigated is added.
By comparing the two, the effects of treatment conditions, reagents, catalysts, light, temperature, pH, and other factors can be evaluated.
The important point in a control experiment is to keep conditions other than the one being investigated as consistent as possible.
If sample amount, temperature, reaction time, pH, concentration, solvent amount, or measurement conditions differ, it becomes impossible to determine which factor caused the difference in the results.
In addition, a positive control is useful for confirming that the experimental system is functioning correctly, while a negative control is useful for checking for background reactions or contamination.
In a report, rather than simply writing that “it was different from the control,” organize and discuss the conditions of the control group and experimental group, the factor being compared, the direction and magnitude of the difference, variation in measured values, reproducibility, positive and negative controls, limitations of the conclusion, and points for improvement.
Discussion of control experiments is an essential part of drawing correct conclusions from experimental results.
