Parameter is a characteristic of:(a) Population(b) Sample(c) Probability distribution(d) Both (a) & (b)

Break Down the Problem

1. Identify what a 'parameter' refers to in statistical terms.
2. Analyze the given options: population, sample, probability distribution.

Relevant Concepts

• A parameter is a numerical value that characterizes a certain attribute of a population.
• In statistics:
  • Population refers to the entire group being studied.
  • Sample is a subset of the population.
  • Probability distribution describes how values of a random variable are distributed.

Analysis and Detail

1. Parameter in Population: It represents a characteristic of the whole population, such as the population mean (μ) or population standard deviation (σ).
2. Parameter in Sample: Samples also have statistics that estimate parameters, but these statistics themselves are generally not considered parameters.
3. Probability Distribution: While parameters like mean or variance can describe probability distributions, they don't constitute a parameter themselves.

Verify and Summarize

• From the analysis, a parameter is specifically associated with the entire population and sometimes with samples to estimate the characteristics of the population.

Final Answer

The correct answer is (a) Population. Parameters typically describe attributes of a population, while statistics describe samples.