Question
In which way could the results of an experiment have bias? when samples sizes are large an outlier data point is present when sample sizes are chosen at random data that has been evaluated for accuracy
Answer
4.6
(242 Votes)
Nancy
Veteran · Tutor for 10 years
Answer
Bias in the results of an experiment can arise in various ways:1. **Sample Size Influence:** Bias may occur when sample sizes are large if the selection process favors a particular group or if there's a systematic exclusion of certain individuals.2. **Outlier Presence:** The presence of an outlier data point can introduce bias, especially if it significantly impacts the overall results. Outliers may distort the true representation of the data.3. **Random Sampling Issues:** While random sampling is generally a good practice to reduce bias, it doesn't guarantee elimination of bias. If the randomization process is flawed or not truly random, bias may still be present in the selected sample.4. **Accuracy Evaluation Bias:** If the process used to evaluate the accuracy of the data is biased or flawed, it can introduce bias into the results. This could happen if the evaluation method itself is not objective or if there's a systematic error in the assessment.In conclusion, bias can manifest in various stages of an experiment, from sample selection to data evaluation, and it's crucial to carefully consider and control these factors to ensure the reliability and validity of the results.