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DATASET'24 Quizz (Round 1)

Total questions: 20

Worksheet time: 30mins

Name
Class
Date
1.

Which of the following is the main purpose of data normalization?

a)

To convert all features to the same scale

b)

To create new features from the existing ones

c)

To handle missing data

d)

To remove outliers from the dataset

2.

What is the role of the "learning rate" in machine learning algorithms?

a)

It determines how fast the model is trained

b)

It controls the amount of data to be used for training

c)

It determines the number of iterations in the training process

d)

It controls the step size while updating weights during training

3.

Which of the following algorithms is best suited for large datasets with many features?

a)

K-Means Clustering

b)

Logistic Regression

c)

Decision Trees

d)

Support Vector Machines (SVM)

4.

What is the purpose of the "fit()" method in Scikit-learn?

a)

To predict outcomes using a trained model

b)

To initialize a machine learning model

c)

To train the model on the data

d)

To evaluate the model's performance

5.

What is the main objective of data preprocessing in data science?

a)

To increase the complexity of the dataset

b)

To remove irrelevant data

c)

To reduce the dataset size

d)

To make the data suitable for analysis

6.

In a decision tree model, what does a "node" represent?

a)

A splitting rule or condition

b)

A data point in the training set

c)

The final output of the model

d)

A hyperparameter of the algorithm

7.

In a Random Forest, what does "bagging" refer to?

a)

The process of dividing the dataset into training and testing sets

b)

Using a bootstrap sample of the training data to build each tree

c)

Combining results of decision trees in a hierarchical manner

d)

Regularizing the decision trees to avoid overfitting

8.

Which of the following is NOT a common application of Natural Language Processing (NLP)?

a)

Sentiment Analysis

b)

Text Classification

c)

Image Recognition

d)

Machine Translation

9.

What does a box plot visually represent?

a)

Frequency distribution

b)

Measures of central tendency and spread

c)

Probabilities

d)

Data redundancy

10.

Which of the following measures the strength of the relationship between two variables?

a)

Mean

b)

Correlation coefficient

c)

Standard deviation

d)

Variance

11.

Which of these techniques is used to fill missing numerical data in a dataset?

a)

Drop rows

b)

Replace with mean

c)

Replace with random values

d)

Replace with mode

12.

Which type of encoding is used to convert categorical data into binary format?

a)

Ordinal Encoding

b)

One-Hot Encoding

c)

Normalization

d)

Standardization

13.

What is the primary purpose of data science?

a)

To create databases

b)

To extract insights from data

c)

To design websites

d)

To maintain servers

14.

Which step involves cleaning and organizing raw data for analysis?

a)

Data Visualization

b)

Data Preprocessing

c)

Data Collection

d)

Data Modeling

15.

Which language is most commonly used in data science?

a)

Java

b)

Python

c)

C++

d)

HTML

16.

What is Jupyter Notebook commonly used for?

a)

Writing HTML code

b)

Creating interactive Python notebooks for data analysis

c)

Storing large data

d)

Compiling Java programs

17.

What is the measure of central tendency that calculates the average of a data set?

a)

Median

b)

Mode

c)

Mean

d)

Range

18.

What does the term “outlier” mean in a data set?

a)

A data point far away from other points

b)

A point with the same value as others

c)

The most frequent value

d)

The average value

19.

Which of the following methods is used to handle missing values in a data set?

a)

Deleting rows

b)

Replacing with mean/median

c)

Keeping as is

d)

All of the above

20.

What is the process of removing duplicate data entries called?

a)

Data Collection

b)

Data Cleaning

c)

Data Redundancy

d)

Data Merging