Final answer:
Collecting more samples and averaging does not reduce systematic (bias) error because bias occurs when the sample is not selected randomly. Increasing the sample size does not address this issue. Random selection is important to reduce bias.
Step-by-step explanation:
Collecting more samples and averaging does not reduce systematic (bias) error because bias occurs when the sample is not selected randomly with respect to a variable in the study. Simply increasing the sample size does not address this issue. In fact, if the sample is biased, even a larger sample runs the risk of not being representative of the population.
For example, let's say we want to study the average height of adults in a city. If we only collect samples from a specific neighborhood where the average height is known to be higher, the sample would be biased. Averaging more samples from this biased sample would not give us an accurate estimate of the average height of the entire population.
To reduce bias, it's important to ensure that the sample is selected randomly from the population being studied. This helps to ensure that every member of the population has an equally likely chance of being included in the sample.