Census, Nonresponse, and Undercoverage (4.2)
Summary
TLDRThis video delves into the critical issues of non-response and undercoverage in sampling. It explains that while samples should represent the population, challenges arise from non-response, where individuals choose not to participate, and undercoverage, where certain segments of the population are entirely excluded, such as those without phones. The script contrasts sampling with a census, highlighting the importance of addressing these issues for accurate data collection.
Takeaways
- đ A sample is a subset of a population used for examination to draw conclusions about the entire population.
- đ The larger the sample size, the more representative it is likely to be of the population.
- đ A census is a method of surveying every individual in a population, providing more accurate data than a sample.
- đ« Non-response occurs when respondents choose not to be contacted or to answer questions during sampling.
- đ· Undercoverage happens when certain individuals have no chance of being included in the sample, affecting the sample's representativeness.
- đ An example of non-response is when a person hangs up the phone during a random call for sampling.
- đ” An example of undercoverage is when people without a telephone number are unable to be contacted and included in the sample.
- đ€ Sampling issues like non-response and undercoverage can lead to biases and inaccuracies in the data collected.
- đ It's important to be aware of and address the problems associated with sampling to ensure reliable data.
- đČ The script uses the scenario of calling random phone numbers to illustrate the concepts of non-response and undercoverage.
- đ Ensuring a representative sample is crucial for making valid inferences about a population from the data collected.
Q & A
What is the purpose of using a sample in statistical analysis?
-A sample is used to draw conclusions about a population because it is representative of that population. It allows for more manageable and cost-effective data collection compared to studying the entire population.
Why is a larger sample size generally more representative of a population?
-A larger sample size tends to be more representative because it reduces the impact of sampling error and increases the likelihood that the sample accurately reflects the characteristics of the entire population.
What is the difference between a sample and a census?
-A sample is a subset of a population, while a census involves surveying every individual in the population. A census provides complete data but is more resource-intensive, whereas a sample is more practical but may introduce sampling errors.
What is non-response in the context of sampling?
-Non-response occurs when individuals or entities chosen for the sample choose not to participate or provide information, which can introduce bias if the non-respondents differ systematically from those who do respond.
Can you explain undercoverage in sampling?
-Undercoverage refers to the situation where certain members of the population have no chance of being included in the sample. This can happen if the sampling method excludes certain groups, leading to a sample that does not fully represent the population.
Why might a researcher encounter non-response when calling random phone numbers?
-Non-response can occur if the called individual refuses to participate in the interview, hangs up, or is otherwise unable or unwilling to provide the information requested by the researcher.
How does the lack of a telephone affect the potential for undercoverage in phone surveys?
-People without a telephone number are automatically excluded from phone surveys, which can lead to undercoverage if this group represents a significant portion of the population with distinct characteristics.
What are some potential issues with relying solely on a sample to understand a population?
-Relying solely on a sample can lead to issues such as non-response bias, undercoverage, and sampling error, which may result in inaccurate or incomplete conclusions about the population.
How can a researcher address the issue of undercoverage in their sampling strategy?
-A researcher can address undercoverage by using multiple sampling methods, ensuring that the sampling frame is comprehensive, and employing techniques to adjust for known biases in the sample selection process.
What steps can be taken to minimize non-response in a survey?
-Minimizing non-response can involve using incentives, following up with non-respondents, ensuring confidentiality, and designing the survey to be as non-intrusive and relevant as possible to the respondents.
How can the problems of non-response and undercoverage impact the validity of research findings?
-Non-response and undercoverage can impact the validity of research findings by introducing biases that may not accurately reflect the true state of the population, potentially leading to incorrect conclusions or recommendations.
Outlines
đ Understanding Sensus Non-Response and Undercoverage
This paragraph introduces the concepts of sensus non-response and undercoverage in the context of sampling and population studies. It explains that a sample should ideally be representative of the entire population, and that a larger sample size tends to increase this representativeness. The paragraph also contrasts sampling with a census, which involves surveying every individual in a population. The main issues discussed are non-response, where individuals choose not to participate in the survey, and undercoverage, where certain individuals have no chance of being included in the sample, such as people without a telephone number in a study relying on phone calls. The paragraph uses the example of a researcher calling random phone numbers to illustrate these concepts, pointing out the three possible outcomes: successful interview, non-response due to refusal, and non-inclusion due to lack of a phone number, which exemplifies undercoverage.
Mindmap
Keywords
đĄSample
đĄPopulation
đĄCensus
đĄNon-response
đĄUndercoverage
đĄRepresentativeness
đĄSampling
đĄResearcher
đĄPhone Number
đĄInterview
đĄFeasibility
Highlights
A sample is part of the population taken out for examination to draw conclusions about the population.
A larger sample size tends to be more representative of the population.
A census surveys every person of a population for more accurate data.
Sampling problems include non-response and undercoverage.
Non-response occurs when respondents choose not to be contacted or answer.
Undercoverage happens when people have no chance of being included in the sample.
Calling random phone numbers can result in three possibilities: interview, non-response, or non-existent number.
People who pick up the phone and allow themselves to be interviewed are part of the sample.
Hanging up the phone is an example of non-response.
A non-existent phone number is an example of undercoverage.
Not everyone has a phone number, leading to undercoverage for those without a telephone.
The importance of being aware of sampling problems for accurate population data.
Representativeness of a sample is crucial for drawing valid conclusions about the population.
Census data is more accurate but not always feasible due to resource constraints.
Sampling methods must account for potential non-response and undercoverage to ensure data quality.
The video discusses strategies for addressing non-response and undercoverage in sampling.
Understanding the limitations of sampling is essential for interpreting results accurately.
The video provides insights into the challenges of obtaining representative samples.
Transcripts
in this video we will be talking about
sensus non-response and undercoverage
recall that a sample is part of the
population that is taken out for
examination we use a sample to draw
conclusions about the population because
it should be representative of the
population the larger the sample size
the more representative it tends to be
of the
population an even more accurate way of
getting data about a population is by
taking a census a census surveys each
and every person of a
population however we have to be aware
of the problems about sampling in
general when we are sampling we cannot
force someone to give us information the
respondents can choose not to be
contacted or can choose not to answer
this is called non-response on the other
hand we can have people in a population
that have absolutely no chance of being
included in the sample
this is called
undercoverage for example if a
researcher wants to gather a sample by
calling random phone numbers there are
three
possibilities the first possibility is
that the other person picks up the phone
and allows him or herself to be
interviewed and be part of the sample
the second possibility is that the other
person just hangs up the phone this
would be non-response because they are
choosing not to answer the third
possibility is that the phone number
does not exist
the researcher can call as many phone
numbers as he wants but the problem is
is that not everyone has a phone number
because they do not own a telephone as a
result people that don't own a telephone
have no chance of being included in the
sample this would be an example of
undercoverage
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