Descriptive analysis is primarily concerned with:

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BlackTom AI · Accepted Answer

Topic at hand: Descriptive analysis and what it focuses on in data analysis.
Option 1: 'Testing hypotheses between groups.' This is typically the realm of inferential statistics, where we compare groups to see if observed differences are statistically significant. Descriptive analysis does not involve hypothesis testing, so this option describes a different objective.
Option 2: 'Describing the basic features of the data collected.' This aligns with descriptive analysis, which centers on summarizing and detailing characteristics such as central tendency, dispersion, and distribution shapes of the dataset. It aims to convey a clear picture of the data without making inferences beyond it.
Option 3: 'Identifying errors in coding.' While data cleaning and checking coding accuracy can be important, identifying coding errors is a preprocessing or data validation task, not the core aim of descriptive analysis itself. It may occur during data preparation, but it does not define descriptive analysis.
Option 4: 'Drawing conclusions about a population based on a sample.' This describes inferential statistics, where conclusions about a larger population are made from a sample using probability theory and confidence intervals. Descriptive analysis does not generalize beyond the observed data in this way.
In summary, option 2 directly captures the essence of descriptive analysis by focusing on summarizing and describing the dataset’s fundamental features, while the other options pertain to inferential reasoning, data quality tasks, or population-level generalizations that lie outside descriptive analysis’s primary scope.

Descriptive analysis is primarily concerned with:

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