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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