MCQ on Errors in Statistics




Statistical errors refer to inaccuracies or variations in data analysis due to flawed methods, sample size limitations, or random fluctuations, potentially leading to incorrect conclusions or predictions in research or decision-making. With this MCQ on Errors in Statistics will help you to understand the concept of Type I and Type II errors in statistics and their implications.

You may also like: Statistical Errors Notes  |  PPT on Statistical Errors



What is a Type I error in statistical hypothesis testing?

What is the probability of committing a Type I error?

What is a Type II error in statistical hypothesis testing?

What is the probability of committing a Type II error?

Which error is more serious when conducting a clinical trial?

What is the relationship between Type I and Type II errors?

Which error is controlled by choosing an appropriate significance level?

What is the consequence of setting a higher significance level (α) in hypothesis testing?

What is the consequence of increasing the sample size in hypothesis testing?

Which error can be reduced by increasing the power of a statistical test?

What is the formula for power in hypothesis testing?

Which error is associated with a small sample size in hypothesis testing?

What is the consequence of increasing the effect size in hypothesis testing?

Which error is more likely to occur in situations where the sample size is large?

You may also like: Biostatistics Notes  |  Biostatistics PPT  |  Biostatistics MCQs  |




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Related posts:

  1. Type I and Type II Errors in Statistics (with PPT)
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