Final answer:
A journalist could estimate the population proportion as a parameter from their survey data by dividing the number of 'yes' responses by the total number of responses. This calculation results in a statistic, not a parameter, as it comes from a sample.
Step-by-step explanation:
A journalist collected data from the first question of their survey and now wishes to estimate a parameter. A parameter that the journalist could estimate is the proportion of respondents who gave a particular answer to the survey question. For instance, if the question was 'Do you read a newspaper daily?', and the journalist collected responses from a sample of people, the parameter could be the true proportion of all people who read a newspaper daily.
To calculate this estimate, the journalist could tally the number of 'yes' responses and divide by the total number of responses collected. If 150 out of a sample of 300 people said 'yes', the estimate of the parameter (proportion of people who read a newspaper daily) would be 150/300 = 0.5, or 50%. This estimate is not the parameter itself, as it is derived from a sample, not the entire population. It is, rather, a statistic used to infer what the true parameter might be.
In statistical terminology, a statistic is a characteristic of a sample, whereas a parameter is a characteristic of a population. The value derived from the sample data (the statistic) serves as an estimate and may subsequently be used to make generalizations about the whole population through inferential statistics.