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Workflow

  1. Define Your Question: Before you start the analysis, you should know what you're looking for. This could be a specific question or a general idea of what you want to know.

  2. Gather Your Data: This could be collecting your own data or finding an existing dataset that fits your needs.

  3. Clean Your Data: This involves handling missing or inconsistent data and may involve removing outliers.

  4. Explore Your Data: This involves using statistical techniques to learn about the relationships between variables.

  5. Analyze Your Data: Apply statistical or machine learning methods to answer your question.

  6. Interpret Your Results: Make sure you understand what your analysis is telling you. This could involve statistical tests for significance, or it could be as simple as comparing the means of two groups.

Example​

// Load your data
const data = readFileSync('path_to_your_data.json', 'utf8')
const dataset = JSON.parse(data)
const column = 'name_of_the_column_to_analyse'

// Clean your data
const cleanedData = dataset.filter(item => item[column] !== null)

// Explore your data
const mean =
  cleanedData.reduce((sum, item) => sum + item[column], 0) / cleanedData.length

// Analyze your data
const variance =
  cleanedData.reduce((sum, item) => sum + Math.pow(item[column] - mean, 2), 0) /
  cleanedData.length

// Interpret your results
console.log(`Mean: ${mean}, Variance: ${variance}`)