Precision in parameter estimation is influenced by sample size; the larger the sample, the more precise the estimate. (See the Wednesday 17 January lecture recording, minutes 36:40-37:40, and Friday 19 January lecture recording, minutes 27:00-32:40.) When we are estimating population proportions with confidence intervals, finding a sample size large enough to achieve a specific level of precision focuses on the margin of error (ME) If we set the margin of error to our desired level of precision and identify a value of that corresponds with a particular confidence level (e.g., 1.96 for a 95% confidence level), we can rearrange the equation above to solve the sample size large enough to guarantee our predetermined level of precision: However, this calculation also requires us to input a value of the unknown parameter p on the right side of the equation. In such cases, we often use a value of p=0.5. If we use this value, it is because _____. (Select all that apply.) Group of answer choices 0.5 is a worst-case value we have a prior estimate of the population proportion we have no prior estimate of the population proportion the margin of error is largest when p is 0.5