Population
A population is the entire set of individuals or observations that are of interest in a particular study.
It includes all members of a defined group that we are studying or collecting information on.
Characteristics
Size: Populations can be finite (e.g., all patients in a hospital) or infinite (e.g., all possible measurements of a particular variable).
Parameters: Descriptive measures that summarize aspects of a population (e.g., mean, variance) are called parameters.
Example
In a study investigating the average blood pressure of adults in a city, the population would be all adults living in that city.
Sample
Definition
A sample is a subset of individuals or observations selected from the population.
Samples are used to make inferences about the population without having to study the entire group.
Characteristics
Representativeness: A good sample accurately reflects the characteristics of the population.
Size: The number of observations in a sample is called the sample size (n).
Statistics: Descriptive measures that summarize aspects of a sample (e.g., sample mean, sample variance) are called statistics. These statistics are used to estimate population parameters.
Example
If we select 100 adults from the city to measure their blood pressure, this group of 100 adults is our sample.
Errors in Sampling
1. Sampling Error
The difference between the sample statistic and the actual population parameter it estimates.
It arises due to the fact that a sample is only a subset of the population.
2. Non-Sampling Error
Errors not related to the act of sampling.
These can include