To answer this question, we need to carefully understand the differences between sample variance and population variance.
1. Population Variance:
- Population variance (denoted as [tex]\(\sigma^2\)[/tex]) is a measure that describes the spread of the entire population's data points. In this case, it pertains to all 950 students.
2. Sample Variance:
- Sample variance is calculated from a subset or sample of the population data (in this scenario, 77 students), and it serves as an estimate of the population variance.
Given the context:
- Population variance relates to the entire population, which is all 950 students, not just the sample of 77 students.
- The problem specifies that we are interested in the population variance, [tex]\(\sigma^2\)[/tex], which inherently is a parameter for the entire population.
Based on this understanding, the correct answer is:
C. 950
This means the population variance [tex]\(\sigma^2\)[/tex] is the variance of the heights of all 950 students, not the sample of 77 students.
