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The data validation process included: Standardization of units (currency conversions, volume units, inflation adjustments) Cross-verification of data points across multiple secondary sources Normalization of inconsistent datasets Identification and resolution of data gaps Outlier detection and removal through algorithmic and manual checks Plausibility and coherence checks across segments and geographies This ensured that the dataset used for modelling was clean, robust, and reliable

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One-fifth of respondents attained a tertiary education level, while 70% of respondents were aged 2564 years (Table 1)

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