Which statement correctly differentiates a parameter from a statistic?

Which statement correctly differentiates a parameter from a statistic?

• A. A parameter describes the population, while a statistic describes the sample.
• B. A parameter describes the sample, while a statistic describes the population.
• C. Both describe populations.
• D. Both describe samples.

Answer: (A)

In statistics, a parameter is a fixed, often unknown value that describes a feature of the entire population. For example, the population mean (mu) or the population standard deviation (sigma) are parameters. A statistic, by contrast, is a number computed from the data you actually collected in a sample; it can vary from sample to sample. The population is the whole group of interest, while the sample is just the subset you observe. So the statement that a parameter describes the population and a statistic describes the sample is the correct distinction. The other ideas mix up which level each term describes (parameters for populations, statistics for samples) or claim both describe the same level, which isn’t accurate. It’s also common to use a statistic to estimate a parameter, but the key idea is that parameters pertain to the population and statistics pertain to the sample.

In statistics, a parameter is a fixed, often unknown value that describes a feature of the entire population. For example, the population mean (mu) or the population standard deviation (sigma) are parameters. A statistic, by contrast, is a number computed from the data you actually collected in a sample; it can vary from sample to sample. The population is the whole group of interest, while the sample is just the subset you observe.

So the statement that a parameter describes the population and a statistic describes the sample is the correct distinction. The other ideas mix up which level each term describes (parameters for populations, statistics for samples) or claim both describe the same level, which isn’t accurate. It’s also common to use a statistic to estimate a parameter, but the key idea is that parameters pertain to the population and statistics pertain to the sample.