What potential pitfalls should be considered when calculating averages in PHP based on historical data?

When calculating averages in PHP based on historical data, potential pitfalls to consider include data outliers skewing the average, missing or incomplete data affecting the accuracy of the average, and the need to handle different data types appropriately. To address these pitfalls, it's important to clean the data by removing outliers, handling missing values, and ensuring consistent data types before calculating the average. 

// Sample PHP code snippet to calculate the average after cleaning the data

$data = [10, 20, 30, null, 40, 50]; // Sample historical data with potential pitfalls

// Remove null values from the data
$data = array_filter($data, function($value) {
    return $value !== null;
});

// Calculate the average of the cleaned data
$average = array_sum($data) / count($data);

echo "Average: " . $average;

Keywords

data validation array manipulation floating point precision statistical calculations error handling

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