For a quantitative study: Topic- Affordable Housing in the United States
o Do the descriptive questions seek to describe responses to major variables?,
o Do the inferential questions seek to compare groups or relate variables?,
o Do the inferential questions follow from a theory?,
o Are the variables positioned consistently from independent to dependent in the
inferential questions?,
o Describe the data source – What instrument used? How is the sample selected?
What is the scale of measurement? What statistical tool is used for analysis?
o What research design was used and how were the results analyzed?
o Describe the findings, limitations, and suggestions for future research
- Affordable Housing in the United State
Title: Housing Affordability Trends
Descriptive Questions
Yes, the descriptive questions aim to illustrate key variables such as:
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What proportion of U.S. households are housing cost-burdened (spending >30% of income on housing)?
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What are the demographics of those applying for affordable housing?
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How does housing waitlist length vary by state or city?
These help quantify the scope and distribution of the affordable housing issue.
Inferential Questions
Yes, inferential questions are used to compare and relate variables:
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Does income level predict housing cost burden?
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Is there a significant difference in housing access between urban and rural residents?
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How does education level correlate with access to subsidized housing?
These allow for statistical analysis of relationships and group comparisons.
Theory Connection
Yes, questions are grounded in Housing Affordability Theory and Urban Spatial Theory, which address systemic economic and geographic influences on housing access.
Variable Positioning
Variables are consistently positioned:
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Independent: income, location, race, education
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Dependent: cost burden, housing access, waitlist time
Data Source & Measurement
Affordable Housing in the United States
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Instrument: Online survey and secondary data from HUD and the American Housing Survey
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Sampling: Stratified random sample of 1,000 U.S. households by income and region
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Measurement Scales:
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Nominal (e.g., region)
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Ordinal (e.g., income brackets)
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Ratio (e.g., percentage of income spent on rent)
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Statistical Tools: SPSS; t-tests, chi-square, regression, correlation analysis
Research Design & Analysis
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Design: Cross-sectional survey design with mixed-methods support
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Analysis: Descriptive stats to summarize; inferential stats to test hypotheses and relationships
Findings, Limitations, and Future Research
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Findings:
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Lower-income and minority groups experience higher housing burdens
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Urban residents face longer waitlists
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Income and education predict access to assistance programs
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Limitations:Affordable Housing in the United States
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Self-report bias
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Limited regional diversity
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Lack of longitudinal data
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Future Research:
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Longitudinal studies
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Regional case studies
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Impact of recent housing policy shifts
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