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Example Data Analysis flashcards
What is a dataset in data analysis?
A collection of structured or unstructured data values (records, observations) organized for analysis, typically stored in tables, files, or databases.
Define a query in the context of data analysis.
A request for information from a dataset using specific syntax (SQL, pandas, etc.) that filters, transforms, or aggregates data to answer a question.
What is the difference between filtering and aggregating data?
Filtering selects rows meeting specific conditions (e.g., WHERE age > 25); aggregating combines rows into summary statistics (e.g., SUM, COUNT, MEAN).
Explain what a JOIN operation does in SQL.
A JOIN combines rows from two or more tables based on a related column, producing a single result set that merges data from multiple sources.
What is the purpose of GROUP BY in data queries?
GROUP BY organizes rows into groups by one or more columns, allowing aggregate functions to compute statistics for each group separately.
Define dimensionality in data analysis.
Dimensionality refers to the number of features/variables in a dataset; high dimensionality means many columns, low means few columns.
What is a pivot table and what problem does it solve?
A pivot table reshapes data by rotating rows into columns and applying aggregations, allowing quick summarization of relationships between multiple variables.
Explain the concept of data normalization in analysis.
Normalization scales numeric features to a standard range (typically 0-1 or z-score), making features comparable and improving algorithm performance.
What is correlation and how does it differ from causation?
Correlation measures the strength and direction of a linear relationship between two variables; causation means one variable directly causes changes in another (correlation ≠ causation).
Define statistical significance and explain why it matters in data analysis.
Statistical significance indicates whether an observed result is unlikely due to random chance (p-value < 0.05); it determines if findings are reliable for decision-making.
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