Why is sample size important in experimental design? A. Larger sample sizes increase the likelihood that the sample is a good representation of the whole population. B. Nobody will have confidence in your results if the sample size is too small. C. A smaller sample size ensures that measurements within a treatment group will be similar. D. Sample size must always be equal among treatment and control groups.

Answer: A

Step-by-step explanation: when Constructing a confidence interval, it is important to take note of the margin of error which is given by the formulae below

Margin of error = critical value * σ/√n.

Where n is the sample size.

As we can see that the critical value is a constant and the population standard deviation.

Hence there is an inverse relationship between margin of error and sample size, which implies that a large sample size produces a small margin of error.

If the margin of error is small, it means the sample size will increase the like hood that the sample is a good representation of the population.