To solve this problem, we need to identify the key statistical terms based on the context of the survey. The "sample" refers to the subset of the population that was surveyed, the "population" is the entire group we are interested in, the "statistic" is a numerical value that describes a characteristic of the sample, and the "parameter" is a numerical value that describes a characteristic of the population.
- Sample: The group of 35 Oxnard College students who were surveyed.
- Population: All students in Oxnard College.
- Statistic: The average number of classes taken by the 35 students surveyed (2.6 classes).
- Parameter: The average number of classes taken by all students in Oxnard College (2 classes).
The sample refers to the specific group of individuals surveyed in the study. In this case, the sample is the 35 Oxnard College students who were surveyed.
\[
\text{Sample} = 35 \text{ students}
\]
The population encompasses all individuals that the study aims to understand. Here, the population consists of all students enrolled at Oxnard College.
\[
\text{Population} = \text{All students in Oxnard College}
\]
The statistic is a numerical value derived from the sample that describes a characteristic of that sample. For this survey, the average number of classes taken by the surveyed students is given as 2.6.
\[
\text{Statistic} = \bar{x} = 2.6 \text{ classes}
\]
The parameter is a numerical value that describes a characteristic of the entire population. According to the survey, the average number of classes taken by all students in Oxnard College is stated to be 2.
\[
\text{Parameter} = \mu = 2 \text{ classes}
\]
- Sample: \( 35 \text{ students} \)
- Population: All students in Oxnard College
- Statistic: \( \bar{x} = 2.6 \text{ classes} \)
- Parameter: \( \mu = 2 \text{ classes} \)
Thus, the answers are:
- Sample: \( \boxed{35} \)
- Population: \( \boxed{\text{All students in Oxnard College}} \)
- Statistic: \( \boxed{2.6} \)
- Parameter: \( \boxed{2} \)