Final answer:
The relationship between a sample and a statistic parallels that between a population and a parameter.Option C is the correct answer.
Step-by-step explanation:
The relationship between a sample and a statistic parallels that between a population and a parameter. A sample is a subset of the population, whereas a statistic is a numerical characteristic of the sample. Similarly, a population is the entire group of interest, while a parameter is a numerical characteristic of the population.
For example, if you want to estimate the average height of all students in a school, you can take a sample of students and calculate their average height. The calculated average height is the sample statistic, which is used to estimate the population parameter, which is the true average height of all students in the school.
The relationship between a sample and a statistic parallels that between a population and a parameter.
A sample is a subset of a population that is studied, and a statistic is a numerical characteristic of the sample. For example, the average score of a math class (sample) is a statistic that estimates the average score of all math classes (population). Similarly, a parameter is a numerical characteristic of the entire population. The aim of inferential statistics is to use the sample statistic to make an inference about the population parameter, which we cannot measure directly.