Final answer:
To improve random assignment efficacy, a large participant pool is essential, allowing for a more accurate representation of the population and minimizing chance errors and bias. Random sampling creates a fair selection process, and blinding helps in reducing experimenter bias.
Step-by-step explanation:
The best way to improve the effectiveness of random assignment is by having a large pool of participants. A larger sample size reduces the likelihood of chance error, represents the population more accurately, and helps ensure that there are no systematic differences between the groups before the experiment. It is critical in experimental design to have randomly selected participant pools, so that every individual has the same probability of being included, thereby mitigating the risk of bias converging from uncontrolled lurking variables.
Random sampling is an effective strategy because it gives every person in the population an equal chance of being chosen, ensuring that the sample represents the broader population appropriately. On the other hand, experimenter and participant blinding is necessary to eliminate experimenter bias, wherein the researcher's expectations inadvertently influence the outcomes. Random assignment coupled with adequate sample sizes and blinding protocols contributes to the reliability and validity of the study's results.