To understand which number of members surveyed could result in a parameter rather than a sample statistic, we need to differentiate between these two terms:
1. Parameter: A parameter is a value that describes a characteristic of an entire population. When we calculate a parameter, it means that we have included every member of the population in our computation.
2. Sample Statistic: A sample statistic is a value that describes a characteristic of a subset of the population. This subset is referred to as a sample.
Given the population consists of 6300 people, let's analyze the provided options:
A. 63: Surveying 63 members of the population represents a sample. This value would be considered a sample statistic because it does not encompass the whole population—only a subset of it.
B. 6300: Surveying all 6300 members of the population means we have included every individual in our calculation. This value constitutes a parameter because it represents data from the entire population.
C. Both 63 and 6300: As previously described, only surveying 6300 members encompasses the entire population, resulting in a parameter. Surveying 63 members does not.
D. Neither 63 nor 6300: This option implies that neither 63 nor 6300 would result in a parameter. However, as we established, surveying 6300 members would indeed result in a parameter.
Therefore, the correct answer is:
B. 6300
