Class 11 Computer Science · Chapter 5 · Test 3
Clustering and Data Visualization
44 MCQs Covers building and evaluating statistical models, linear and logistic regression, clustering and K-means, and ethics. Also covers data visualization (bar, line, histogram, scatterplot, boxplot, Excel/Sheets) with all 8 exercise MCQs.
44 questions · 40 min · 44 marks
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Sample questions
The first 5 of 44. Try each one, then tap to see the answer.
Question 1
Statistical modeling is used to:
- AClean data
- BMake sense of data and predict outcomes
- CTransform data
- DCollect data
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Answer: B
Models show relationships and predict the future.
Question 2
The first step in building a statistical model is:
- ACollecting data
- BEvaluating the model
- CChoosing an algorithm
- DDefining the problem
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Answer: D
We must know what we want to predict.
Question 3
Which is an example of a statistical model?
- ALinear regression
- BData cleaning
- CData transformation
- DData collection
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Answer: A
Linear regression predicts one variable from another.
Question 4
Training a model means:
- ARemoving errors
- BCollecting new data
- CTeaching the model using data
- DCalculating mean
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Answer: C
The model learns from collected data.
Question 5
Evaluating a model involves:
- ACollecting more data
- BTesting the model with new data
- CCleaning the data
- DCalculating variance
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Answer: B
We check if predictions are correct.
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