Question at position 11 Only two treatments should be used in an experiment.Each shrub did not receive all ten pruning methods.Pruning methods were not randomly assigned to shrubs.Each pruning method was used on only one shrub.The shrubs were not randomly selected.

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BlackTom AI · Accepted Answer

In this scenario, there are several potential design weaknesses to consider, and each option points to a different issue with the experiment.
Option 1: 'Only two treatments should be used in an experiment.' This statement is a prescriptive rule about how many treatments to include, but it does not inherently describe a flaw present in the described setup. The problem is not that there should be only two treatments; it’s that context matters and the number of treatments alone isn’t the core issue here.
Option 2: 'Each shrub did not receive all ten pruning methods.' This indicates that not every shrub experienced every method, which could be a design choice to avoid carryover or to limit exposure. However, it is not necessarily a fatal flaw; it could be acceptable depending on the research aims and the randomization plan. The key question is whether this lack of full treatment exposure undermines the comparison, which might or might not be the case.
Option 3: 'Pruning methods were not randomly assigned to shrubs.' Lack of random assignment increases the risk of systematic bias, as preexisting differences between shrubs could be confounded with pruning methods. This is a valid concern and undermines internal validity because it makes it harder to attribute any observed effects to the pruning methods rather than to shrub differences.
Option 4: 'Each pruning method was used on only one shrub.' This is a critical flaw because it provides no replication for any pruning method. With only a single shrub per method, any observed effect could be due to the unique characteristics of that shrub rather than the method itself, making causal inferences unreliable. This severely limits the ability to generalize results and to disentangle shrub effects from method effects.
Option 5: 'The shrubs were not randomly selected.' Nonrandom selection of shrubs introduces selection bias, which threatens external validity and may skew results if chosen shrubs differ systematically from the broader population. This is a concern, but in terms of core experimental design, the lack of replication for each treatment (Option 4) is a more fundamental flaw for establishing causality.
Overall, while several options point to legitimate issues, the statement that 'Each pruning method was used on only one shrub' identifies a fundamental lack of replication and a major threat to internal validity, making it the strongest design flaw described. Maintaining random assignment (Option 3) and addressing selection bias (Option 5) are important, but without replication per treatment, the conclusions about pruning method effects would be unreliable regardless of other controls.

Question at position 11 Only two treatments should be used in an experiment.Each shrub did not receive all ten pruning methods.Pruning methods were not randomly assigned to shrubs.Each pruning method was used on only one shrub.The shrubs were not randomly selected.

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