Introduction to Sampling Distribution

Parameter is the numerical characteristic of _____________.

• Sample

• Population

• Standard Deviation

• Variance

It is the numerical characteristic of a sample.

• Mean

• Variance

• Parameter

• Statistic

If the population is countable, we call it _________.

• Finite

• Infinite

• Discrete

• Continuous

If the population is not countable, we call it __________.

• Finite

• Infinite

• Continuous

• Discrete

Which of the following is the best example of statistic?

• Mean

• Population variance

• Sample Standard Deviation

• Variace

It is a technique in selecting n elements from a population with size N. Samples are repeatedly drawn from a population.

• Random Variable

• Random Sampling

• Sampling Technique

• Research

It is a process of selecting n sample size in the population via random number or through lottery method.

• Simple Random Sampling

• Stratified Random Sampling

• Systematic Random Sampling

• Cluster Random Sampling

The process of dividing the population into subgroups or ‘strata’ and drawing members at random from each subgroup or ‘strata’.

• Simple Random Sampling

• Stratified Random Sampling

• Systematic Random Sampling

• Cluster Random Sampling

It is a process of selecting the kth element in the population until the desired number of subjects or respondents is attained.

• Simple Random Sampling

• Stratified Random Sampling

• Systematic Random Sampling

• Cluster Random Sampling

It is a process of selecting clusters from a population which is very large or widely spread out over a wide geographical area.

• Simple Random Sampling

• Stratified Random Sampling

• Systematic Random Sampling

• Cluster Random Sampling