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SayPro Data Analysis: Identify correlations between these issues and their impact on specific groups (e.g., low-income families, vulnerable populations, etc.).

Email: info@saypro.online Call/WhatsApp: + 27 84 313 7407

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SayPro Data Analysis: Correlations & Impact on Specific Groups


1. Objective

  • To identify relationships between community issues and assess their differential impact on vulnerable or specific population groups.

2. Data Preparation

  • Segment data by demographic variables (income level, age, gender, location, vulnerability status).
  • Ensure data completeness and consistency for subgroup analysis.

3. Correlation Analysis

Issue Pair / Variable 1Variable 2 / GroupStatistical Test / MethodCorrelation Coefficient / StrengthSignificance (p-value)Interpretation / Insights
Unemployment RateLow-Income Families (%)Pearsonโ€™s r / Chi-square test0.65 (strong positive)<0.01Higher unemployment strongly linked with low-income households
Access to HealthcareVulnerable PopulationsLogistic RegressionOdds Ratio 2.3<0.05Vulnerable groups 2.3 times less likely to access healthcare
School EnrollmentRural vs Urban ChildrenT-test / ANOVADifference significant<0.05Rural children have significantly lower enrollment rates
Water Pollution ExposureHouseholds near industrial sitesSpatial Correlation AnalysisHigh spatial correlation<0.01Proximity to industry strongly linked to pollution exposure

4. Impact Assessment by Group

Population GroupIssues Most ImpactfulQuantitative Impact MetricsQualitative Insights / QuotesRecommendations for Targeted Interventions
  • Neftaly Malatjie | CEO | SayPro
  • Email: info@saypro.online
  • Call: + 27 84 313 7407
  • Website: www.saypro.online

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