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Chapter 2: Problem 1

With respect to a research study, what is meant by a population? What is a sample?

Short Answer

Expert verified
A population includes all individuals of interest in a study, while a sample is a smaller subset of that population used to draw conclusions.

Step by step solution

01

Understanding Population

The population in a research study refers to the entire group of individuals or instances that the research is interested in. For example, if studying students' test scores, all the students in the school form the population.
02

Defining Sample

A sample is a subset of the population that is selected for the actual study. This smaller group is used to draw conclusions about the entire population. For instance, taking 100 students from the school to analyze test scores is creating a sample.
03

Connection Between Population and Sample

The sample should ideally represent the population accurately so that the conclusions drawn can be generalized to the whole population. Various sampling methods are used to achieve a representative sample, such as random sampling.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Population in Research
The term 'population' in research refers to the entire pool of individuals, events, or elements that a researcher is interested in studying. It encompasses everyone or everything that fits the criteria set out by the research study. For example, if you are studying the dietary habits of teenagers in a city, the population would be all the teenagers living in that particular city.
Understanding the population is crucial because the aim of any research is to make conclusions that can be applied to the whole population.
When defining a population, be specific about the characteristics you are focusing on. Doing so helps ensure that the research is both effective and reliable.
Sample in Research
In research, a 'sample' refers to a smaller, manageable segment of the population that is selected for the actual study. Think of it as a miniature model of the population.
For example, surveying 200 teenagers from the city to understand their dietary habits would be your sample.
This subgroup should accurately reflect the characteristics of the entire population to allow reliable insights. The validity of research hinges on how well the sample represents the population.
Using a well-designed sampling strategy helps in obtaining results that can be generalized to the whole population.
Sampling Methods
Sampling methods are techniques used to select a sample from the population. The goal is to ensure that the sample accurately represents the population, enhancing the validity and reliability of the research findings. Common sampling methods include:
  • Random Sampling: Every individual in the population has an equal chance of being selected. This reduces bias and increases the representativeness of the sample.
  • Stratified Sampling: The population is divided into subgroups (strata) based on shared characteristics. Samples are then drawn from each stratum. This method ensures that specific subgroups are adequately represented.
  • Cluster Sampling: The population is divided into clusters, often based on geographic areas. A random sample of clusters is chosen, and all individuals within these clusters are included in the sample. This method is cost-effective and practical for large, dispersed populations.
  • Systematic Sampling: Individuals are selected at regular intervals from an ordered list. While easy to implement, it may introduce bias if there is a hidden pattern within the list.
Choosing the right sampling method depends on the research objectives, population size, and available resources. A well-chosen method enhances the accuracy and applicability of the research results.

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