MCQs

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Overall MCQs for Reference

In machine learning, a Type 2 error is also known as:
a. False Positive
b. False Negative
c. True Positive
d. True Negative
Answer: b. False Negativecodecrucks+2
A Type 2 error occurs when:
a. A true null hypothesis is rejected
b. A false null hypothesis is not rejected
c. An alternative hypothesis is accepted when it is false
d. A test statistic is significant
Answer: b. A false null hypothesis is not rejectedtestbook+3
Which scenario illustrates a Type 2 error in medical testing?
a. Diagnosing a healthy person as sick
b. Failing to diagnose a sick person
c. Correctly diagnosing all sick persons
d. Incorrectly approving a drug
Answer: b. Failing to diagnose a sick persongeeksforgeeks+1
What is the probability of making a Type 2 error called?
a. Alpha
b. Beta
c. Gamma
d. Delta
Answer: b. Betainvestopedia+1
Which strategy typically reduces Type 2 errors in a model?
a. Increasing sample size
b. Lowering significance level
c. Ignoring outliers
d. Reducing training epochs
Answer: a. Increasing sample sizelibretexts+1
Type 2 error rate increases if the statistical power of a test:
a. Increases
b. Decreases
c. Remains unchanged
d. Is set to 1
Answer: b. Decreasesencord+1
Which of the following is NOT a cause of Type 2 error?
a. Small sample size
b. Low test power
c. High effect size
d. Incorrect model selection
Answer: c. High effect sizetestbook+1
In hypothesis testing, which error involves failing to reject the null hypothesis when it is false?
a. Type 1 error
b. Type 2 error
c. Type 3 error
d. No error
Answer: b. Type 2 errorwikipedia+2
An example of Type 2 error in manufacturing is:
a. Recalling a good product
b. Accepting a defective product
c. Selling only defective items
d. Testing only non-defective products
Answer: b. Accepting a defective productcorporatefinanceinstitute+1
Which term describes failing to detect an existing bug during software testing?
a. Type 1 error
b. Type 2 error
c. Type 3 error
d. Type 4 error
Answer: b. Type 2 erroramplitude
To minimize Type 2 errors, one should:
a. Reduce alpha level
b. Increase sample diversity
c. Increase statistical power
d. Use fewer data samples
Answer: c. Increase statistical powerencord+1
When conducting a hypothesis test, the consequences of a Type 2 error can be described as:
a. False alarm
b. Missed detection
c. Accurate prediction
d. Overfitting
Answer: b. Missed detectionscribbr+2
Which of the following is synonymous with a Type 2 error?
a. False Positive
b. False Negative
c. True Negative
d. True Positive
Answer: b. False Negativecodecrucks+2
In court cases, a Type 2 error corresponds to:
a. Convicting an innocent person
b. Acquitting a guilty person
c. Ignoring the evidence
d. Overturning a verdict
Answer: b. Acquitting a guilty personbyjus+2
The impact of raising the threshold for positive predictions in classification is likely to:
a. Decrease Type 2 errors
b. Increase Type 2 errors
c. Eliminate all errors
d. Cause random errors
Answer: b. Increase Type 2 errorsencord
Which of the following methods helps reduce false negatives?
a. Lowering decision threshold
b. Increasing model complexity
c. Shuffling test data
d. Removing features
Answer: a. Lowering decision thresholdencord
In statistical analysis, Type 2 error can be reduced by:
a. Increasing the power of the test
b. Decreasing batch size
c. Lowering model accuracy
d. Using only training data
Answer: a. Increasing the power of the testinvestopedia+1
When is a Type 2 error most problematic?
a. In fraud detection
b. In positive sentiment analysis only
c. When classes are balanced
d. If all hypotheses are accepted
Answer: a. In fraud detectionscribbr+1
Type 2 error is more likely when:
a. Effect size is small
b. Effect size is large
c. Model is overfitted
d. Hypothesis is true
Answer: a. Effect size is smalltestbook+1
The probability of avoiding a Type 2 error in hypothesis testing is known as:
a. Sensitivity
b. Power
c. Significance level
d. Beta risk
Answer: b. Powerwikipedia+2
Which method can increase the power of a test and thus reduce Type 2 errors?
a. Increasing sample size
b. Lowering alpha
c. Ignoring beta
d. Using double-blind design
Answer: a. Increasing sample sizeinvestopedia
Type 2 errors are especially relevant in:
a. Binary classification tasks
b. Unsupervised learning
c. Reinforcement learning
d. Clustering algorithms
Answer: a. Binary classification tasksexploredatabase+1
In fraud detection, missing a fraudulent transaction is an example of:
a. Type 1 error
b. Type 2 error
c. No error
d. Both types
Answer: b. Type 2 errorscribbr+1
In which situation does a Type 2 error NOT occur?
a. Correctly rejecting a false null hypothesis
b. Incorrectly accepting a true null hypothesis
c. Incorrectly failing to reject a false null hypothesis
d. Correctly accepting a true null hypothesis
Answer: a. Correctly rejecting a false null hypothesislibretexts+2
Which error occurs when the null hypothesis is true but rejected?
a. Type 1 error
b. Type 2 error
c. Type 3 error
d. No error
Answer: a. Type 1 errorgeeksforgeeks+2
Type 2 error is most associated with which kind of result?
a. False positive
b. True negative
c. False negative
d. True positive
Answer: c. False negativecodecrucks+2
Which metric is directly affected by Type 2 errors in a confusion matrix?
a. Precision
b. Recall
c. F1-score
d. Accuracy
Answer: b. Recallkdnuggets+1
Beta in statistical risk refers to:
a. The probability of Type 1 error
b. The probability of Type 2 error
c. The power of the test
d. The size of effect
Answer: b. The probability of Type 2 errorwikipedia+1
Type 2 error occurs under which hypothesis condition?
a. Null hypothesis is true and rejected
b. Null hypothesis is false and accepted
c. Alternative hypothesis is false and rejected
d. Alternative hypothesis is true and accepted
Answer: b. Null hypothesis is false and acceptedexploredatabase+1
In a medical diagnostic model, missing an actual case of disease is classified as:
a. Type 1 error
b. Type 2 error
c. Type 3 error
d. None
Answer: b. Type 2 errorgeeksforgeeks
Which is more severe in safety-critical ML applications, if undetected?
a. Type 1 error
b. Type 2 error
c. Data leakage
d. No error
Answer: b. Type 2 errorscribbr+1
A test’s sensitivity is inversely related to the occurrence of:
a. Type 2 errors
b. Type 1 errors
c. True positives
d. True negatives
Answer: a. Type 2 errorskdnuggets+1
A Type 2 error occurs when a statistical test:
a. Unable to reject a true null hypothesis
b. Unable to reject a false null hypothesis
c. Fails to accept a true null hypothesis
d. Fails to reject a true alternative hypothesis
Answer: b. Unable to reject a false null hypothesistestbook+2
Which action increases the risk of Type 2 error?
a. Using a very low sample size
b. Overfitting the training data
c. Setting a high alpha level
d. Shuffling the labels randomly
Answer: a. Using a very low sample sizeinvestopedia+1
The mathematical notation for the probability of Type 2 error is:
a. α
b. β
c. λ
d. σ
Answer: b. βwikipedia+1
In hypothesis testing, failing to detect a real effect is known as:
a. Type 1 error
b. Type 2 error
c. Model drift
d. Feature selection error
Answer: b. Type 2 errorlibretexts+2
Type 2 errors are minimized by:
a. Increasing effect size
b. Reducing sample size
c. Decreasing experiment duration
d. Ignoring data imbalance
Answer: a. Increasing effect sizetestbook+1
Which of these errors is more likely when a test lacks sensitivity?
a. Type 1 error
b. Type 2 error
c. Data leakage
d. Model bias
Answer: b. Type 2 errorencord
Type 2 error can lead to which consequence in product quality testing?
a. Production delay
b. Releasing defective products
c. Increasing costs
d. Satisfying regulations
Answer: b. Releasing defective productscorporatefinanceinstitute+1
A hypothesis test with high beta risk implies which result?
a. More likely to detect real effects
b. Fewer false negatives
c. Increased risk of missing actual effects
d. Higher precision
Answer: c. Increased risk of missing actual effectsinvestopedia+1
Minimizing Type 2 errors is critical in which context?
a. Spam email filtering
b. Network security threat detection
c. Weather prediction
d. Sports analytics
Answer: b. Network security threat detectionencord
In ML model evaluation, which metric is directly lowered by Type 2 errors?
a. Precision
b. Recall
c. Specificity
d. Data variance
Answer: b. Recallencord
Choosing a very stringent p-value (alpha) can increase:
a. Type 1 errors
b. Type 2 errors
c. Both errors
d. No errors
Answer: b. Type 2 errorskdnuggets+1
Which example best describes a Type 2 error in facial recognition?
a. Recognizing the wrong person
b. Failing to recognize a known person
c. Detecting everyone correctly
d. Flagging all faces as unrecognized
Answer: b. Failing to recognize a known personwikipedia
In null hypothesis significance testing, Type 2 error means:
a. Detecting effect when none exists
b. Missing real effect when it exists
c. Both
d. Neither
Answer: b. Missing real effect when it existslibretexts+2
Which class imbalance situation is likely to cause more Type 2 errors?
a. Majority class is positive
b. Minority class is negative
c. Classes are equal
d. No class imbalance
Answer: b. Minority class is negativeencord
The probability of avoiding a Type 2 error is represented by:
a. Power
b. Sensitivity
c. Beta risk
d. Significance level
Answer: a. Powerinvestopedia+1
Which design change is NOT effective for reducing Type 2 error?
a. Increasing power
b. Using larger samples
c. Augmenting rare class examples
d. Lowering model complexity
Answer: d. Lowering model complexityinvestopedia+1
In terms of error rates, a Type 2 error is also called:
a. False Accept Rate (FAR)
b. False Match Rate (FMR)
c. False Reject Rate (FRR)
d. False Non-Match Rate (FNMR)
Answer: b. False Match Rate (FMR)wikipedia
If you want to lower the probability of a Type 2 error in diagnostic ML, you should:
a. Use stricter significance threshold
b. Increase relevant data samples
c. Train on fewer examples
d. Ignore model calibration
Answer: b. Increase relevant data samplesinvestopedia+1

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