MCQs

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Overall MCQs for Reference

1. Which one generalizes a sample to a whole population?
   a. Descriptive statistics
   b. Inferential statistics
   c. Predictive analytics
   d. Exploratory analysis
   Answer: b. Inferential statisticsincludehelp​
2. What does inferential statistics use to make predictions about populations?
   a. Data visualization
   b. Sampling
   c. Model tuning
   d. Feature scaling
   Answer: b. Samplingappliedaicourse​
3. Which of these is NOT a method of inferential statistics?
   a. Hypothesis testing
   b. Regression analysis
   c. Mean calculation
   d. Confidence intervals
   Answer: c. Mean calculationappliedaicourse​
4. The process of inferring properties about a population based on sample data is called:
   a. Classification
   b. Statistical inference
   c. Dimensionality reduction
   d. Feature selection
   Answer: b. Statistical inferencewikipedia​
5. The entire group being studied in inferential statistics is called the:
   a. Population
   b. Sample
   c. Dataset
   d. Distribution
   Answer: a. Populationgeeksforgeeks​
6. A subset of the population used for analysis is called:
   a. Sample
   b. Cohort
   c. Margin
   d. Statistic
   Answer: a. Samplegeeksforgeeks​
7. Point estimation provides:
   a. Interval of values
   b. A single value estimate
   c. Range of values
   d. No values
   Answer: b. A single value estimategeeksforgeeks​
8. Interval estimation offers:
   a. Just a mean
   b. A likely interval
   c. Specific outcome
   d. Infinite possibilities
   Answer: b. A likely intervalgeeksforgeeks​
9. In hypothesis testing, the default assumption is known as:
   a. Alternative hypothesis
   b. Null hypothesis
   c. Composite hypothesis
   d. Directional hypothesis
   Answer: b. Null hypothesisappliedaicourse​
10. What is a p-value used for?
    a. Measuring dispersion
    b. Quantifying uncertainty
    c. Measuring mean difference
    d. Calculating mode
    Answer: b. Quantifying uncertaintyappliedaicourse​
11. Which method estimates a population parameter using a range?
    a. Point estimation
    b. Confidence interval
    c. Linear regression
    d. Data imputation
    Answer: b. Confidence intervalsimplilearn​
12. Which of the following distributions is central to inferential statistics?
    a. Uniform distribution
    b. Normal distribution
    c. Beta distribution
    d. Exponential distribution
    Answer: b. Normal distributionappliedaicourse​
13. When analyzing large samples, what law supports inferential statistics?
    a. Law of Averages
    b. Central Limit Theorem
    c. Law of Large Numbers
    d. Law of Small Numbers
    Answer: b. Central Limit Theoremw3schools​
14. Confidence interval expresses:
    a. Data spread
    b. Estimation’s reliability
    c. Relationship between variables
    d. Feature importance
    Answer: b. Estimation’s reliabilitysimplilearn​
15. Which is used for testing if two groups’ means are different?
    a. t-test
    b. Chi-square test
    c. ANOVA
    d. Regression
    Answer: a. t-testappliedaicourse​
16. Hypothesis testing in machine learning helps in:
    a. Feature engineering
    b. Model validation
    c. Data cleaning
    d. Visual analysis
    Answer: b. Model validationappliedaicourse​
17. The process of dividing the population by certain characteristics is called:
    a. Sampling
    b. Stratification
    c. Clustering
    d. Grouping
    Answer: b. Stratification360digitmg​
18. If p-value < significance level, then:
    a. Accept null hypothesis
    b. Reject null hypothesis
    c. Accept alternative hypothesis directly
    d. Ignore results
    Answer: b. Reject null hypothesisgeeksforgeeks​
19. Z-test is best for:
    a. Small samples (<30)
    b. Large samples (>30)
    c. Categorical data
    d. Non-normal data
    Answer: b. Large samples (>30)geeksforgeeks​
20. What method helps understand relationship between variables?
    a. Regression analysis
    b. ANOVA
    c. Histogram
    d. Boxplot
    Answer: a. Regression analysisappliedaicourse​
21. To compare means of multiple groups, use:
    a. ANOVA
    b. t-test
    c. Median test
    d. Proportion test
    Answer: a. ANOVAsimplilearn​
22. In inferential statistics, sample statistics estimate:
    a. Population parameters
    b. Data features
    c. Model accuracy
    d. Outliers
    Answer: a. Population parametersappliedaicourse​
23. The parameter estimated by regression is called:
    a. Mode
    b. Coefficient
    c. Probability
    d. Feature importance
    Answer: b. Coefficientsimplilearn​
24. Non-parametric tests are used when:
    a. Data is normally distributed
    b. Data is categorical or not normally distributed
    c. Variance is zero
    d. Samples are large
    Answer: b. Data is categorical or not normally distributed360digitmg​
25. What is used to generalize findings from a sample to a population?
    a. Inferential statistics
    b. Data visualization
    c. Feature engineering
    d. Algorithm selection
    Answer: a. Inferential statisticsappliedaicourse​
26. In machine learning, inferential statistics aids:
    a. Hyperparameter tuning
    b. Model generalization
    c. Data labeling
    d. Execution speed
    Answer: b. Model generalizationappliedaicourse​
27. Which of the following is NOT required for inferential statistics?
    a. Sampling techniques
    b. Probability theory
    c. Performance metrics
    d. Population definition
    Answer: c. Performance metricsgeeksforgeeks​
28. What type of statistics involves making inferences about populations?
    a. Descriptive
    b. Inferential
    c. Quantitative
    d. Qualitative
    Answer: b. Inferentialgeeksforgeeks​
29. Which test assesses categorical variable relationships?
    a. t-test
    b. Chi-square test
    c. Z-test
    d. ANOVA
    Answer: b. Chi-square testananjanmaiti​
30. The null hypothesis typically proposes:
    a. Difference exists
    b. No effect or no difference
    c. High correlation
    d. Strong causation
    Answer: b. No effect or no differenceappliedaicourse​
31. Which is a probabilistic machine learning algorithm using Bayesian inference?
    a. Decision tree
    b. Naive Bayes
    c. KNN
    d. SVM
    Answer: b. Naive Bayesappliedaicourse​
32. If the data violate normality assumptions, which test is preferred?
    a. t-test
    b. Non-parametric test
    c. ANOVA
    d. Z-test
    Answer: b. Non-parametric test360digitmg​
33. Sampling error refers to:
    a. Error in hypothesis
    b. Difference due to sample selected
    c. Error in model
    d. Incorrect feature selection
    Answer: b. Difference due to sample selectedgeeksforgeeks​
34. What aids creation of prediction intervals in regression?
    a. Descriptive statistics
    b. Inferential statistics
    c. Data transformation
    d. Dimensionality reduction
    Answer: b. Inferential statisticssimplilearn​
35. Which method is used for estimating population variance from sample variance?
    a. F-test
    b. t-test
    c. Z-test
    d. Regression
    Answer: a. F-testananjanmaiti​
36. Type I error in hypothesis testing is:
    a. Accepting true null hypothesis
    b. Rejecting false null hypothesis
    c. Rejecting true null hypothesis
    d. Accepting alternative hypothesis
    Answer: c. Rejecting true null hypothesisappliedaicourse​
37. Type II error is:
    a. Accepting a false null hypothesis
    b. Rejecting true null hypothesis
    c. Correctly rejecting null hypothesis
    d. None of these
    Answer: a. Accepting a false null hypothesisappliedaicourse​
38. Parameter estimation in statistics is crucial for:
    a. Feature extraction
    b. Testing model accuracy
    c. Generalizing conclusions
    d. Data normalization
    Answer: c. Generalizing conclusionssimplilearn​
39. Inferential statistics in machine learning does NOT generally involve:
    a. Summarizing sample data
    b. Making predictions on unseen data
    c. Estimating population parameters
    d. Hypothesis testing
    Answer: a. Summarizing sample dataappliedaicourse​
40. When inferential statistics are used to support ML models, they:
    a. Prove model correctness
    b. Quantify uncertainty
    c. Remove outliers
    d. Normalize data
    Answer: b. Quantify uncertaintysimplilearn​
41. In comparing sample mean to population mean, which test applies if population variance is unknown?
    a. t-test
    b. Z-test
    c. ANOVA
    d. Chi-square
    Answer: a. t-testgeeksforgeeks​
42. The confidence level most often used in statistical inference is:
    a. 50%
    b. 90%
    c. 95%
    d. 99%
    Answer: c. 95%ananjanmaiti​
43. Sample statistics are used to infer:
    a. Individual outcome
    b. Population statistics
    c. Model hyperparameters
    d. Data shape
    Answer: b. Population statisticsgeeksforgeeks​
44. The Central Limit Theorem states that larger samples:
    a. Increase noise
    b. Produce normal distribution of sample means
    c. Lead to model bias
    d. Increase sample variance
    Answer: b. Produce normal distribution of sample meansgeeksforgeeks​
45. Inferential statistics helps machine learning models to be:
    a. More computationally costly
    b. Generalizable to new data
    c. Less interpretable
    d. Faster to train
    Answer: b. Generalizable to new dataappliedaicourse​
46. Statistical power in inference refers to:
    a. Likelihood of error
    b. Probability of correctly rejecting null hypothesis
    c. Model training time
    d. Strength of dataset
    Answer: b. Probability of correctly rejecting null hypothesissimplilearn​
47. Bayesian inference differs by:
    a. Ignoring prior probability
    b. Updating probabilities with evidence
    c. Using only frequentist methods
    d. Not applying to machine learning
    Answer: b. Updating probabilities with evidenceappliedaicourse​
48. Bootstrapping in statistics refers to:
    a. Fixed sample analysis
    b. Resampling technique for accuracy estimation
    c. Preprocessing step
    d. Feature selection
    Answer: b. Resampling technique for accuracy estimationsimplilearn​
49. Which of the following does NOT use inferential statistics?
    a. Creating summary tables
    b. Hypothesis testing
    c. Model evaluation
    d. Confidence interval estimation
    Answer: a. Creating summary tablessimplilearn​
50. In ML, inferential statistics allows for:
    a. Perfect classification
    b. Making data-driven predictions about population
    c. Feature extraction
    d. Deterministic conclusions
    Answer: b. Making data-driven predictions about populationgeeksforgeeks+2​t population**interviewkickstart+2​

1. https://www.includehelp.com/mcq/statistics-in-data-science-multiple-choice-questions-mcqs.aspx
2. https://www.appliedaicourse.com/blog/statistics-for-machine-learning/
3. https://en.wikipedia.org/wiki/Statistical_inference
4. https://www.geeksforgeeks.org/machine-learning/statistics-for-machine-learning/
5. https://www.simplilearn.com/inferential-statistics-article
6. https://www.w3schools.com/ai/ai_statistics.asp
7. https://360digitmg.com/blog/inferential-statistics-interview-questions
8. https://www.geeksforgeeks.org/quizzes/inferential-statistics-1/
9. https://www.geeksforgeeks.org/data-science/what-is-inferential-statistics/
10. https://ananjanmaiti.com/data-science-descriptive-inferential-statistics-interview-questions-answers/
11. https://testbook.com/objective-questions/mcq-on-inferential-data-analysis–5fc43460a1bc541cc2000260
12. https://www.sanfoundry.com/data-science-questions-answers-introduction-statistical-inference/
13. https://interviewkickstart.com/blogs/articles/data-science-mcq-answers
14. https://testbook.com/objective-questions/mcq-on-inferential-and-descriptive-statistics–66a78aac0ed97b16bd3312aa
15. https://www.interviewbit.com/machine-learning-mcq/
16. https://itfeature.com/hypothesis/mcqs-on-statistical-inference-9/
17. https://www.scribd.com/document/605976704/QUESTION-ON-INFERENTIAL-STATISTICS
18. https://www.examveda.com/computer-science/practice-mcq-question-on-machine-learning/
19. https://www.datacamp.com/blog/statistics-interview-questions
20. https://365datascience.com/resources-center/practice-exams/fundamentals-of-inferential-statistics/