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Many students who study using our platform have reported that a large number of the practice questions here are very similar to those that appear in real exams. View Courses
Many students who study using our platform have reported that a large number of the practice questions here are very similar to those that appear in real exams. View Courses
Harshit is working with a large dataset that would be exceptionally burdensome to analyze line-by-line. He decides to break up the dataset. Each entry is now equally likely to be selected at random. This is an example of what?
Correct Answer: b) Simple Random Sampling
Simple Random Sampling is a statistical method where each entry in a dataset has an equal probability of being selected. Since Harshit is randomly selecting from his dataset with equal likelihood, this matches the definition of Simple Random Sampling.
Incorrect Answers:
Stratified Random Sampling – Involves dividing data into specific groups (strata) before sampling to ensure representation. Harshit did not categorize his data into groups, so this is incorrect.
Data Reduction – Focuses on reducing the size of a dataset by removing redundant or unnecessary data, which is different from randomly selecting entries for analysis.
Data Aggregation – Involves combining data from multiple sources or summarizing data (e.g., calculating averages or totals). Harshit is sampling, not aggregating.
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