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Overall MCQs for Reference

  1. What is a Type 1 error commonly referred to as?
    a. True negative
    b. False positive
    c. True positive
    d. False negative
    Answer: b. False positivetestbook+4​
  2. Which hypothesis does a Type 1 error wrongly reject?
    a. Alternative hypothesis
    b. Null hypothesis
    c. Research hypothesis
    d. Testing hypothesis
    Answer: b. Null hypothesiswikipedia+3​
  3. What is the usual symbol for the probability of a Type 1 error?
    a. β (beta)
    b. μ (mu)
    c. α (alpha)
    d. δ (delta)
    Answer: c. α (alpha)testbook+1​
  4. A Type 1 error indicates what kind of result?
    a. False alarm
    b. Missed detection
    c. Correct acceptance
    d. Correct rejection
    Answer: a. False alarmdatasciencecentral+1​
  5. In a medical test, a Type 1 error would result in:
    a. Missing a real disease
    b. Diagnosing a disease that doesn’t exist
    c. Correctly finding disease
    d. Correctly missing disease
    Answer: b. Diagnosing a disease that doesn’t existencord+1​
  6. Type 1 error in machine learning is also known as:
    a. Alpha error
    b. Beta error
    c. Gamma error
    d. Delta error
    Answer: a. Alpha errorcorporatefinanceinstitute+1​
  7. What consequence can a Type 1 error produce in fraud detection?
    a. Missing real fraudsters
    b. Accusing innocent people of fraud
    c. Detecting all fraudsters
    d. Ignoring all fraud
    Answer: b. Accusing innocent people of fraudencord+1​
  8. Which parameter is adjusted to control Type 1 error in hypothesis testing?
    a. Power
    b. Significance level
    c. Effect size
    d. Sample mean
    Answer: b. Significance levelwikipedia+1​
  9. What does setting a lower significance level (α) do for Type 1 error probability?
    a. Increases probability
    b. Decreases probability
    c. Has no effect
    d. Doubles the probability
    Answer: b. Decreases probabilitytestbook+1​
  10. Which term describes Type 1 error in classification?
    a. True positive
    b. False negative
    c. False positive
    d. True negative
    Answer: c. False positivekaggle+1​
  11. The risk of Type 1 error is most common in which procedure?
    a. Regression analysis
    b. Hypothesis testing
    c. Data normalization
    d. Feature engineering
    Answer: b. Hypothesis testinggeeksforgeeks+1​
  12. What can help reduce Type 1 errors in a machine learning model?
    a. Lower decision threshold
    b. Higher decision threshold
    c. Ignore threshold
    d. Random prediction
    Answer: b. Higher decision thresholdencord​
  13. Type 1 error occurs when a model:
    a. Misses existing patterns
    b. Finds patterns that don’t exist
    c. Never predicts positive class
    d. Always predicts negative class
    Answer: b. Finds patterns that don’t existtestbook+1​
  14. Which of these is synonymous with Type 1 error?
    a. False negative
    b. False positive
    c. True positive
    d. True negative
    Answer: b. False positivecodecrucks+1​
  15. In statistics, Type 1 error deals with:
    a. Failing to reject a false hypothesis
    b. Incorrectly rejecting a true hypothesis
    c. Correctly accepting a true hypothesis
    d. Incorrectly accepting a false hypothesis
    Answer: b. Incorrectly rejecting a true hypothesiskdnuggets+2​
  16. If α = 0.01, the probability of Type 1 error is:
    a. 10%
    b. 1%
    c. 0.1%
    d. 0.01%
    Answer: b. 1%wikipedia+1​
  17. In a court analogy, a Type 1 error equates to:
    a. Freeing a guilty
    b. Convicting an innocent
    c. Prosecuting the guilty
    d. Ignoring crime
    Answer: b. Convicting an innocentcodecrucks+1​
  18. Which confusion matrix component reflects Type 1 errors?
    a. False negatives
    b. True positives
    c. False positives
    d. True negatives
    Answer: c. False positiveskaggle+1​
  19. Reducing the alpha level in testing will:
    a. Increase Type 1 errors
    b. Decrease Type 1 errors
    c. No effect on errors
    d. Remove Type 2 errors
    Answer: b. Decrease Type 1 errorswikipedia+1​
  20. Type 1 errors are also called:
    a. Beta errors
    b. Type II errors
    c. Alpha errors
    d. Type III errors
    Answer: c. Alpha errorscorporatefinanceinstitute+1​
  21. A Type 1 error in spam detection happens when:
    a. Legitimate emails marked as spam
    b. Spam emails not detected
    c. All emails marked as valid
    d. Spam emails always detected
    Answer: a. Legitimate emails marked as spamdatasciencecentral+1​
  22. The Type 1 error is related to which test statistic outcome?
    a. Within critical region
    b. Outside critical region
    c. No effect
    d. Random region
    Answer: a. Within critical regiongeeksforgeeks+1​
  23. A low Type 1 error rate is desirable because:
    a. Results are more reliable
    b. Errors occur quickly
    c. Models run slowly
    d. Data is less used
    Answer: a. Results are more reliablekdnuggets+1​
  24. Which real-world scenario is affected by Type 1 errors?
    a. Medical treatment
    b. Weather prediction
    c. Sports analytics
    d. Fashion trends
    Answer: a. Medical treatmentgeeksforgeeks+1​
  25. Type 1 error is a mistake in:
    a. Accepting null hypothesis when true
    b. Rejecting null hypothesis when true
    c. Accepting null hypothesis when false
    d. Rejecting null hypothesis when false
    Answer: b. Rejecting null hypothesis when truegeeksforgeeks+2​
  26. The relationship between α and the likelihood of Type 1 error is:
    a. Directly proportional
    b. Inversely proportional
    c. No relationship
    d. U-shaped
    Answer: a. Directly proportionaltestbook+1​
  27. Why is Type 1 error critical in model evaluation?
    a. Overstates model’s capability
    b. Understates model’s capability
    c. Balances both errors
    d. Has no effect
    Answer: a. Overstates model’s capabilitykdnuggets+1​
  28. Type 1 error is statistically known as:
    a. Positive error
    b. False alarm
    c. Miss detection
    d. True error
    Answer: b. False alarmdatasciencecentral+1​
  29. Type 1 error probability is set before testing as:
    a. Significance level (α)
    b. Sample size
    c. p-value
    d. Confidence interval
    Answer: a. Significance level (α)wikipedia+1​
  30. An example of Type 1 error in bankruptcy prediction:
    a. Predicting bankruptcy when company is solvent
    b. Missing bankrupt company
    c. Ignoring solvent company
    d. Never predicting bankruptcy
    Answer: a. Predicting bankruptcy when company is solventencord​
  31. Which statement is true about Type 1 errors?
    a. They are false positives
    b. They are false negatives
    c. They are true negatives
    d. They are true positives
    Answer: a. They are false positiveskaggle+4​
  32. When is a Type 1 error made in hypothesis testing?
    a. When true null hypothesis is rejected
    b. When false null hypothesis is accepted
    c. When alternative hypothesis is accepted
    d. When alternative hypothesis is rejected
    Answer: a. When true null hypothesis is rejectedgeeksforgeeks+1​
  33. What is the impact of high Type 1 error for quality control?
    a. Many defects found, even in good items
    b. Defects always missed
    c. All items passed
    d. Inspections skipped
    Answer: a. Many defects found, even in good itemsencord+1​
  34. Type 1 error in fraud analytics means:
    a. Honest transactions flagged as fraud
    b. Fraudulent transactions passed
    c. All transactions marked valid
    d. No fraud detected
    Answer: a. Honest transactions flagged as fraudkdnuggets+1​
  35. Which of the following is not a consequence of Type 1 error?
    a. False positive detection
    b. Wasting resources on wrong predictions
    c. Ignoring real patterns
    d. Overestimating risk
    Answer: c. Ignoring real patternskdnuggets+1​
  36. By decreasing α, we:
    a. Reduce Type 1 errors
    b. Increase Type 1 errors
    c. Eliminate Type 2 errors
    d. Affect training data size
    Answer: a. Reduce Type 1 errorstestbook+1​
  37. Type 1 error is not:
    a. Avoidable by changing α
    b. The same as Type 2 error
    c. False positive
    d. Error of commission
    Answer: b. The same as Type 2 errorwikipedia+1​
  38. Which setting needs careful management to avoid Type 1 errors?
    a. Training loss
    b. Decision threshold
    c. Feature selection
    d. Scalability constraints
    Answer: b. Decision thresholdencord​
  39. Who is at risk due to Type 1 error in health analytics?
    a. Healthy patients misdiagnosed
    b. Ill patients left untreated
    c. Doctors
    d. No one
    Answer: a. Healthy patients misdiagnosedgeeksforgeeks+1​
  40. If significance level α is increased, what happens to Type 1 error likelihood?
    a. Increases
    b. Decreases
    c. Remains constant
    d. Error disappears
    Answer: a. Increasestestbook+1​
  41. Which error is opposite to Type 1 error?
    a. Beta error
    b. Type II error
    c. Type III error
    d. Gamma error
    Answer: b. Type II errorcodecrucks+2​
  42. What is compromised when Type 1 error is high?
    a. Model reliability
    b. Training time
    c. Data quality
    d. Model cost
    Answer: a. Model reliabilitykdnuggets+2​
  43. Type 1 error in access control can cause:
    a. Unauthorized access granted
    b. Authorized access denied
    c. Data not updated
    d. No effect
    Answer: b. Authorized access deniedkaggle+1​
  44. Which term best relates to Type 1 error?
    a. Error of omission
    b. Error of commission
    c. Sampling error
    d. Model complexity
    Answer: b. Error of commissionwikipedia​
  45. Type 1 error in facial recognition means:
    a. Face flagged as match when no match exists
    b. Face never detected
    c. All faces passed
    d. Data always matched
    Answer: a. Face flagged as match when no match existskaggle+2​
  46. What does α = 0.05 represent regarding Type 1 error?
    a. 5% chance of false detection
    b. 50% chance of false detection
    c. No chance of false detection
    d. Variable probability
    Answer: a. 5% chance of false detectiontestbook+1​
  47. Which is not a characteristic of Type 1 error?
    a. False positive
    b. Occurs when null hypothesis is true
    c. Controlled by setting α
    d. Occurs when null hypothesis is false
    Answer: d. Occurs when null hypothesis is falsegeeksforgeeks+2​
  48. What is the effect of lowering Type 1 error in model validation?
    a. Fewer false alarms
    b. More false alarms
    c. More missed detections
    d. No false alarms
    Answer: a. Fewer false alarmskdnuggets+1​
  49. In machine learning, Type 1 error is problematic in:
    a. Classification tasks
    b. Feature scaling
    c. Data preprocessing
    d. Model deployment
    Answer: a. Classification taskskaggle+1​
  50. Type 1 error can be best described as:
    a. Incorrectly confirming something exists
    b. Correctly confirming presence
    c. Ignoring real presence
    d. Always predicting negative
    Answer: a. Incorrectly confirming something existsdatasciencecentral+4​
  1. https://testbook.com/objective-questions/mcq-on-type-i-errors–5fc43406a1bc541cc200011e
  2. https://encord.com/glossary/type-1-errors-definition/
  3. https://www.geeksforgeeks.org/data-science/type-i-and-type-ii-errors/
  4. https://www.kdnuggets.com/2022/08/type-type-ii-errors-difference.html
  5. https://www.kaggle.com/general/181960
  6. https://en.wikipedia.org/wiki/Type_I_and_type_II_errors
  7. https://www.alooba.com/skills/concepts/statistics/type-1-error/
  8. https://www.datasciencecentral.com/understanding-type-i-and-type-ii-errors/
  9. https://corporatefinanceinstitute.com/resources/data-science/type-i-error/
  10. https://codecrucks.com/mcq/machine-learning-mcqs-set-01/
  11. https://www.sanfoundry.com/1000-machine-learning-questions-answers/
  12. https://www.scribd.com/document/425850093/ML-mcq
  13. https://www.gyansetu.in/blog/machine-learning-mcq-interview-preparation/
  14. https://towardsdatascience.com/type-i-ii-errors-and-sample-size-calculation-in-hypothesis-testing-760dae42a065/
  15. https://diptisurvase.wordpress.com/wp-content/uploads/2022/09/ml-mcqs.pdf
  16. https://www.interviewbit.com/machine-learning-mcq/
  17. https://www.igmguru.com/blog/machine-learning-mcqs

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