Final answer:
In the study of all 1911 employees at a college, the 45% who own a television represents a parameter, as it involves the entire population. When analyzing a sample, such as a survey of high school seniors, the results are considered a statistic.
Step-by-step explanation:
Understanding Parameters and Statistics
In statistics, the concept of parameters and statistics is pivotal in data analysis. When dealing with parameters, we consider a numerical characteristic that defines a whole population. Conversely, a statistic is a numerical characteristic that describes a sample of the population.
Parameters vs. Statistics in Context
The scenario provided suggests that a study found 45% of all 1911 employees at a college own a television. By definition, since the value is derived from all the employees, this 45% represents a parameter because it is a measure of the entire population of the college's employees.
However, if we consider a scenario such as the U.S. federal government surveying a fraction of high school seniors about their education and employment plans and finding that 50% plan to attend a four-year college, this is a statistic since it is derived from a sample of the total population of high school seniors.
When dealing with studies and surveys, it's crucial to understand whether the data you have is representing a whole population or just a sample. This dictates whether you are calculating parameters or statistics.
Example of Parameter Calculation
A situation where you might calculate a parameter rather than a statistic would be when a school district reviews the final grade averages for all its students in a particular academic year. Since the data covers the entire population of students in the district, any analysis will result in the calculation of parameters.
Following the examples and studies given, we are better equipped to differentiate between a parameter and a statistic and understand their proper application in data analysis and interpretation.