Title Linear Regression Analysis & Predictive Modeling (SPSS) Overview Executed an end-to-end lin...Title Linear Regression Analysis & Predictive Modeling (SPSS) Overview Executed an end-to-end lin...
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Mena Hasan
• 19h
Title
Linear Regression Analysis & Predictive Modeling (SPSS)
Overview
Executed an end-to-end linear regression analysis in SPSS to evaluate relationships between key financial/operational metrics, assess statistical significance, and build predictive models for decision-making.
Key Analysis & Process
Model Fitting & Diagnostics: Evaluated the overall goodness-of-fit ($R$, $R^2$, and Adjusted $R^2$) to quantify how effectively predictor variables account for variance in the target metric.
ANOVA & Significance Testing: Verified model validity using ANOVA testing ($F$-statistic, $p < 0.05$) to ensure observed linear relationships were statistically significant rather than due to random chance.
Coefficient Evaluation: Analyzed unstandardized and standardized ($\beta$) regression coefficients alongside $t$-statistics and $p$-values to measure the directional impact and individual predictive weight of each independent variable.
Assumption Validation: Examined residual distributions and correlation outputs to ensure linear regression assumptions (linearity, normality of residuals, and homoscedasticity) were fully satisfied.
Outcome
Delivered a validated predictive model and actionable statistical outputs, enabling stakeholders to forecast future outcomes based on key data-driven metrics.
Data AnalysisIBM SPSS
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