Answer:
a) Statistic.
b) The population proportion is expected to be between 0.29 and 0.31 with a 94% degree of confidence.
Explanation:
a) The proportion of 30% is a statistic, as it is a value that summarizes data only from the sample taken in the study from USA Today. Other samples may yield different proportions.
b) We can use the statistic to estimate a confidence interval for the parameter of the population.
The standard error for the proportion is calculated as:

The margin of error is 0.01. We can use this value to determine the level of confidence that represents.
The formula for the margin of error is:

This z-value, according to the the standard normal distribution, corresponds to a confidence interval of 94%.
The interval for this margin of error is:

Then, we can conclude that the population proportion is expected to be between 0.29 and 0.31 with a 94% degree of confidence.