Data Science Methodology Class 12 MCQ – The CBSE has updated the syllabus for St. XII (Code 843). The MCQs are made based on the updated CBSE textbook. All the important information is taken from the Artificial Intelligence Class XII Textbook Based on the CBSE Board Pattern.
Data Science Methodology Class 12 MCQ
1. Which is the hardest stage in the foundational methodology of Data Science?
a. Business Understanding
b. Data collection
c. Modelling
d. Evaluation
2. Business Sponsors defines the problem and project objectives from a __ perspective.
a. Economic
b. Feedback
c. Business
d. Data Collection
3. Match the following and choose the correct options:
i. Descriptive approach A. Statistical Analysis
ii. Diagnostic approach B. Current Status
iii. Predictive approach C. How to solve it?
iv. Prescriptive approach D. Probabilities of action
a. (i)—A , (ii)—B, (iii) – C , (iv)—D
b. (i)—B , (ii)—A, (iii) – D , (iv)—C
c. (i)—D , (ii)—B, (iii) – A , (iv)—C
d. (i)—A , (ii)—C, (iii) – B , (iv)—D
4. Arrange the following statements in order
i: Gaps in data will be identified and plans to fill/make substitutions will have to be made
ii: Decisions are made whether the collection requires more data or not
iii: Descriptive statistics and visualization is applied to dataset
iv: Identify the necessary data content, formats and sources
a. i,ii,iii,iv
b. iv,ii,iii,i
c. i,iii,ii,iv
d. ii,i,iii,iv
5. Data Modelling focuses on developing models that are either or _
a. Supervised, Unsupervised
b. Predictive, Descriptive
c. Classification, Regression
d. Train-test split, Cross Validation
6. Statement 1- There is no optimal split percentage
Statement 2- The most common split percentage between training and testing data is 20%-80%
a. Statement 1 is true Statement 2 is false
b. Statement 2 is true Statement 1 is false
c. Both Statement 1 and 2 are true
d. Both Statement 1 and 2 are false
7. Train-test split function is imported from which Python module?
a. sklearn.model_selection
b. sklearn.ensemble
c. sklearn.metrics
d. sklearn. preprocessing
8. Identify the incorrect statement:
i. cross-validation gives a more reliable measure of your model’s quality
ii. cross-validation takes short time to run
iii. cross-validation gets multiple measures of model’s quality
iv. cross-validation is preferred with small data
a. ii and iii
b. iii only
c. ii only
d. ii, iii and iv
9. Identifying the necessary data content, formats and sources for initial data collection is done in which step of Data Science methodology?
a. Data requirements
b. Data Collection
c. Data Understanding
d. Data Preparation
10. Data sets are available online. From the given options, which one does not provide online data?
a. UNICEF
b. WHO
c. Google
d. Edge
11. A __ set is a set of historical data in which outcomes are already known.
a. Training set
b. Test set
c. Validation set
d. Evaluation set
12. _ data set is used to evaluate the fit machine learning model.
a. Training set
b. Test set
c. Validation set
d. Evaluation set
13. x_train,x_test,y_train,y_test = train_test_split (x, y, test_size=0.2)
From the above line of code, identify the training data set size
a. 0.2
b. 0.8
c. 20
d. 80
14. In k-fold cross validation, what does k represent?
a. number of subsets
b. number of experiments
c. number of folds
d. all of the above
15. Identify the correct points regarding MSE given below:
i. MSE is expanded as Median Squared Error
ii. MSE is standard deviation of the residuals
iii. MSE is preferred with regression
iv. MSE penalize large errors more than small errors
a. i and ii
b. ii and iii
c. iii and iv
d. ii, iii and iv
16. During Train-Test split evaluation, we usually split the data around _ between testing and training stages.
a. 90% -— 10%
b. 20% — 80%
c. 100% -—0%
d. 0% — 100%
17. Which of the following is NOT True for Testing ?
a. The volume of test data should be very small.
b. Data validation is important.
c. Your testing team should test the AI and ML algorithms keeping model validation.
d. Your team must create test suites that help you validate your ML models.
18. The first fundamental step, when starting an AI initiative is __ and selecting the relevant use cases, that the AI model will be built to address.
a. scoping
b. deployment
c. thinking
d. designing
19. The train-test procedure is appropriate when there is a sufficiently __ dataset available.
a. small
b. moderate
c. large
d. average
20. The first fundamental step when starting an project.
a. Evaluation
b. Testing
c. Deployment
d. Scoping
29. Expand the term RMSE.
a. Rational Median Square Error
b. Root Median Square Estimate
c. Root Mean Squared Error
d. Root Median Sequential Estimate
30. Which of the following is not True for Testing ?
a. Data validation is important.
b. The volume of test data can be large.
c. Your testing team should test the AI and ML algorithms keeping model validation.
d. Regulatory compliance testing and security testing are not so important.
31. Which of the following are correct ?
a. If the data you collect is not effective AI algorithm.
b. The testing phase is essentially an iterative process.
c. Test data should not include all relevant subsets of training data.
d. Once the relevant projects have been selected and properly scoped, the next step of the machine learning life cycle is testing.
32. Which of the following is true for Train-Test Split Evaluation ?
a. The procedure involves taking a dataset and dividing it into two subsets.
b. The train-test procedure is appropriate when there is a small dataset.
c. The objective is to estimate the performance of the user.
d. It cannot be used for classification or regression problems.
33. Techniques like descriptive statistics and visualisations can be applied to datasets after the original data gathering to analyse the content. To close the gap, additional data collecting may be required. Identify the stage of this analytic approach.
a. Data Requirements
b. Data Gathering
c. Data Understanding
d. Data Preparation
34. Which of the following is a disadvantage of Cross Validation Technique?
a. Cross-validation provides insight into how the model will generalize to a new dataset.
b. Cross-validation aids in determining a more accurate model prediction performance estimate.
c. As we need to train on many training sets, cross-validation is computationally expensive.
d. Cross-validation could result in more precise models.
35. A good model should have an value less than 180.
a. RMSE
b. MSE
(c ) Focal Loss
d. MAE
36. Which of the following is incorrect?
1) Testing data is the one on which we train and fit our model basically to fit the parameters
2) Training data is used only to assess performance of model
3) Testing data is the unseen data for which predictions have to be made
a. 1) and 3) only
b. 1) and 2) only
c. 2) and 3) only
d. 1), 2) and 3)
37. Which of the following are the objectives of the testing team in AI modelling?
1) Model Validation
2) Security compliance
3) Understanding data
4) Minimizing bias
a. (1), (2) and (3)
b. (2), (3) and (4)
c. (1), (3) and (4)
d. (1), (2) and (4)
38. In Design Thinking, phase involves gathering user feedback on the prototypes you’ve created as well as obtaining a better understanding of your users.
a. Prototype
b. Test
c. Ideate
d. Empathize
39. Once you have got an AI model that’s ready for production, AI engineers then a trained model, making it available for external inference requests.
a. Evaluate
b. Test
(c ) Deploy
d. Redesign
40. Data Validation for human biases is conducted in phase of AI Model Life Cycle.
a. Scoping
b. Data Collection
(c ) Design
d. Testing
41. Which of the following is a disadvantage of Cross Validation Technique?
a. Cross-validation provides insight into how the model will generalize to a new dataset.
b. Cross-validation aids in determining a more accurate model prediction performance estimate.
c. As we need to train on many training sets, cross-validation is computationally expensive.
d. Cross-validation could result in more precise models.
42. Which of the following is incorrect?
1) Testing data is the one on which we train and fit our model basically to fit the parameters
2) Training data is used only to assess performance of model
3) Testing data is the unseen data for which predictions have to be made
a. 1) and 3) only
b. 1) and 2) only
c. 2) and 3) only
d. 1), 2) and 3)
43. Which of the following are the objectives of the testing team in AI modelling?
1) Model Validation
2) Security compliance
3) Understanding data
4) Minimizing bias
a. (1), (2) and (3)
b. (2), (3) and (4)
c. (1), (3) and (4)
d. (1), (2) and (4)
44. A researcher wants to study the association between gender and using a mobile phone. Data collected for this study will be __
a. Qualitative data
b. Quantitative data
c. Continuous data
d. Classified data
45. The data scientist will use _ for predictive modelling?
a. Artificial Intelligence
b. Machine Learning
c. Training Set
d. Deep Learning
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