Podcast Beta
Questions and Answers
What characterizes purposive data collection?
Which type of error occurs when the sample does not adequately represent the entire population?
Sampling error is most likely to increase under which condition?
What is a typical reason for nonresponse bias in surveys?
Signup and view all the answers
Which type of data is structured through carefully planned methodologies?
Signup and view all the answers
What happens in adjustment error?
Signup and view all the answers
What does nonresponse error specifically refer to?
Signup and view all the answers
Which of the following best describes organic data?
Signup and view all the answers
What does measurement error in a survey primarily refer to?
Signup and view all the answers
The Pearson correlation coefficient ranges from:
Signup and view all the answers
In the context of correlation, $ ho$ represents:
Signup and view all the answers
What is the null hypothesis (H0) when testing for a correlation greater than zero?
Signup and view all the answers
A large p-value in hypothesis testing indicates:
Signup and view all the answers
As the sample size increases, we expect the standard error to:
Signup and view all the answers
What does the area under the curve in hypothesis testing represent?
Signup and view all the answers
Imputation is a method used to adjust for:
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.
