3.1: Defining Populations and Samples Flashcards
What is a population in the context of research methods and data?
In research, a population refers to the entire group of items or phenomena that share a common characteristic or interest.
What is a sample in research, and how does it relate to a population?
A sample is a subset of a population.
It is used in research when it is impractical or impossible to study the entire population.
Researchers draw conclusions about the population based on the characteristics of the sample.
What is the purpose of selecting a sample in research?
The purpose of selecting a sample is to make inferences about the characteristics of the entire population it represents. Researchers aim to choose a sample that is representative of the population.
Why is it often challenging to study an entire population in research?
It is often challenging because it’s difficult to ensure every member of the population participates in a study, making it impractical or impossible to collect data from everyone.
What is an inference in research, and how is it made?
An inference in research is a conclusion about the characteristics of a population based on the characteristics of a sample.
It is made by extrapolating information gathered from the sample to the entire population.
How does the accuracy of inferences depend on the quality of the sample chosen?
The accuracy of inferences depends on the sample’s representativeness.
If a well-chosen sample closely resembles the population, the inferences will be more accurate.
For example, if 24% of the entire population is closed on Sundays, a good sample should approximate this percentage.
What is a parameter in the context of populations and samples in research?
A parameter is a characteristic or value that describes a population. It represents a specific attribute of the entire population.
What is a statistic in the context of populations and samples in research?
A statistic is a characteristic or value that describes a sample. It represents a specific attribute of the subset of the population that was studied.
Can you provide an example of a parameter and a statistic?
Certainly. In the example of U.S. restaurants and retail stores, the percentage of all U.S. restaurants/retail stores closed on Sundays (e.g., 24%) is a parameter.
If a sample survey shows that 27% of the sampled restaurants/retail stores are closed on Sundays, 27% is a statistic.
How are parameters and statistics related in making inferences about populations?
When we don’t have data for the entire population, we use sample statistics to make inferences about population parameters.
The goal is to estimate population parameters based on the characteristics of the sample
In what situations might organizations have access to population data, and how is it useful in analysis?
Organizations often have access to population data for subsets of their target audience, such as their current customers.
This data is useful for analysis using tools like Power BI or Tableau, and the results obtained are considered parameters because they pertain to the entire known population.
Why is it important to distinguish between parameters and statistics in research and data analysis?
Distinguishing between parameters and statistics is crucial because it helps researchers and analysts understand whether their findings are based on a sample or the entire population.
This distinction affects the validity and generalizability of conclusions drawn from the data.
What are descriptive or summary statistics in the context of statistics and data analysis?
Descriptive or summary statistics are measures that provide information about a group of interest, which can include all visible components of a sample or the entire population if feasible.
They summarize and describe the data.
How do inferential statistics differ from descriptive statistics?
Inferential statistics are measures calculated using a sample of the desired population.
They are used to test hypotheses about the population, whereas descriptive statistics are used to summarize and describe data.
What is a hypothesis, and what role does it play in data analysis and research?
A hypothesis is a proposed explanation or supposition made based on limited evidence.
It serves as a starting point for further investigation in research and data analysis. Hypotheses are used to make predictions and draw conclusions about populations.
