Final answer:
Variables are characteristics that can be measured or observed, while data refers to values collected from a population or sample. An operational definition is a clear explanation of how a variable is measured. A population is the entire group of interest, while a sample is a subset of the population used for analysis.
Step-by-step explanation:
In statistics, variables refer to any characteristic or property that can be measured or observed. They can be classified as independent variables, which are manipulated or controlled, and dependent variables, which are the outcomes or responses that are measured. Data, on the other hand, refers to the values or observations collected from a population or sample. It can be qualitative, such as categories or labels, or quantitative, such as numerical values.
An operational definition is a clear and concise explanation of how a variable is measured or observed. It provides specific criteria or steps to ensure consistency and accuracy in data collection. For example, if a study aims to measure the level of happiness in individuals, an operational definition may define happiness as the average rating on a scale of 1-10 based on a set of predetermined criteria.
A population is the entire group of individuals, objects, or measurements that the researcher is interested in studying. A sample, on the other hand, is a subset of the population that is used to draw conclusions or make inferences about the population. Parameters are numerical characteristics of a population, such as the mean or proportion, while statistics are numerical characteristics of a sample. Parameters are often unknown and estimated using statistics.