4. Probability
Basic Concepts of Probability
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Which of the following are important because they help to ensure data integrity in probability experiments?
A
Biased estimators
B
Random sampling methods
C
Subjective opinions
D
Ignoring outliers
Verified step by step guidance1
Understand the concept of data integrity in probability experiments: Data integrity refers to the accuracy and consistency of data throughout its lifecycle. In probability experiments, ensuring data integrity is crucial for obtaining reliable and unbiased results.
Review the role of random sampling methods: Random sampling methods are essential because they ensure that every member of the population has an equal chance of being selected. This minimizes bias and helps maintain the integrity of the data collected.
Evaluate the impact of biased estimators: Biased estimators can lead to systematic errors in the results, compromising data integrity. Therefore, they are not considered important for ensuring data integrity in probability experiments.
Consider subjective opinions: Subjective opinions are based on personal beliefs or preferences and can introduce bias into the data. They do not contribute to maintaining data integrity in probability experiments.
Analyze the effect of ignoring outliers: Ignoring outliers can sometimes distort the results, but in certain cases, it may be necessary to exclude extreme values to maintain the integrity of the analysis. However, this practice should be applied cautiously and with justification.
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