L7 - Total Survey Error

Podcast

Play an AI-generated podcast conversation about this lesson

Questions and Answers

What characterizes purposive data collection?

A byproduct of daily processes

Randomly selected without a clear purpose

Curated for specific research objectives (correct)

Generated incidentally without a specific goal

Which type of error occurs when the sample does not adequately represent the entire population?

Nonresponse error

Coverage error (correct)

Sampling error

Adjustment error

Sampling error is most likely to increase under which condition?

When the entire population is surveyed

When data is collected incidentally

When non-random sampling methods are applied (correct)

When a larger sample size is used

What is a typical reason for nonresponse bias in surveys?

Systematic differences between respondents and non-respondents Signup and view all the answers

Which type of data is structured through carefully planned methodologies?

Designed data Signup and view all the answers

What happens in adjustment error?

The researcher omits important data weighting Signup and view all the answers

What does nonresponse error specifically refer to?

Refusal to participate in or complete the survey Signup and view all the answers

Which of the following best describes organic data?

It occurs as a byproduct of regular processes Signup and view all the answers

What does measurement error in a survey primarily refer to?

Mistakes made by respondents Signup and view all the answers

The Pearson correlation coefficient ranges from:

-1 to 1 Signup and view all the answers

In the context of correlation, $ ho$ represents:

The correlation in the population Signup and view all the answers

What is the null hypothesis (H0) when testing for a correlation greater than zero?

$ρ=0$ Signup and view all the answers

A large p-value in hypothesis testing indicates:

Strong agreement with the null hypothesis Signup and view all the answers

As the sample size increases, we expect the standard error to:

Decrease Signup and view all the answers

What does the area under the curve in hypothesis testing represent?

The probability of obtaining a more extreme value than observed Signup and view all the answers

Imputation is a method used to adjust for:

Nonresponse to some questions Signup and view all the answers

Study Notes

Data Generation Techniques

Organic data is generated incidentally without specific intention, often a byproduct of regular processes.
Purposive data is collected with a specific research question in mind, structured to meet the study's objectives.
Designed data is generated via controlled methodologies like surveys and experiments, aimed at describing social reality, studying causal relationships, or generalizing to the target population.

Total Survey Error Types

Coverage Error: Occurs when certain population members are excluded from sampling, leading to skewed results if excluded individuals differ from those sampled.
Sampling Error: Arises from surveying a subset of the population; increases with smaller and non-random samples, contributing to uncertainty requiring statistical quantification.
Nonresponse Error: Results from selected individuals refusing participation (unit-nonresponse) or specific questions (item-nonresponse), potentially causing bias if respondents differ systematically from non-respondents.
Adjustment Error: Occurs from improper weighting or handling of data that leads to underrepresentation of certain groups; can be corrected through methods like “weighting” or imputation.
Measurement Error: Arises from faulty responses due to survey design issues or respondent behavior, impacting data integrity.
Processing Error: Involves errors during data collection and processing stages, including data entry and handling mistakes.

Correlation and Hypothesis Testing

Correlation measures the strength and direction of relationships between two variables, with the Pearson correlation coefficient ranging from -1 to +1.
The sampling distribution reflects variability in correlation coefficients (r) across multiple random samples from the same population.
Population correlation is represented by ρ; a larger sample size leads to a smaller standard error.
In the absence of a relationship (ρ=0), sample distributions will be centered at zero, with both positive and negative correlation values observed.

Statistical Hypotheses

Null Hypothesis (H0): Assumes no correlation exists in the population (ρ=0).
Research Hypothesis (Ha/H1): Proposes a positive correlation exists (ρ>0), linking kindness and life satisfaction.
A large p-value indicates strong support for the null hypothesis; a small p-value suggests little support for it.
Chance refers to the probability of observing a sample value as extreme as the one obtained, evaluated using mathematical models and represented by areas under the probability distribution curve.

Studying That Suits You

Use AI to generate personalized quizzes and flashcards to suit your learning preferences.

Description

This quiz focuses on the concept of Total Survey Error, including types of correlational data: organic and purposive. Explore how data is generated incidentally or with specific intentions, and understand the implications of each type for research methodologies. Test your knowledge on the differences and applications of these data types.