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Q.1
In EDA, what is the term for a graphical representation that displays the distribution of two continuous variables?
Scatter Matrix
Scatter Plot
Вox Plot
Violin Plot
(A)
Q.2
What is the primary goal of a bar plot (bar chart) in EDA?
To calculate summary statistics
To display relationships between variables
То compare multiple categories
To visualize the distribution of data
(C)
Q.3
Which EDA technique is used to visualize the distribution of two continuous variables using a matrix of scatter plots?
Histogram Matrix
Scatter Matrix
Bоx Plot Matrix
Correlation Matrix
(B)
Q.4
In EDA, what is the term for a graphical representation that displays the distribution of a continuous variable along with a box?
Heat Map
Scatter Plot
Вox Plot
Violin Plot
(D)
Q.5
What is the primary purpose of a swarm plot in EDA?
To display relationships between variables
To visualize the distribution of data
To compare multiple categories
To identify missing values
(A)
Q.6
In EDA, what is the primary purpose of a line plot (time series plot)?
To display relationships between variables
To visualize the distribution of data
To identify missing values
To calculate summary statistics
(B)
Q.7
What does the term "mode" refer to in the context of data distribution analysis in EDA?
The presence of outliers
The most frequently occurring value
The average value
The spread of data
(B)
Q.8
Which EDA technique is used to visualize the distribution of a single categorical variable as a bar chart?
Scatter Plot
Box Plot
Histogram
Bar Chart
(D)
Q.9
In EDA, what is the primary purpose of a histogram?
To calculate summary statistics
To display relationships between variables
To visualize the distribution of data
To identify missing values
(C)
Q.10
In EDA, what is the term for a graphical representation that displays the distribution of a continuous variable along with outliers?
Heat Map
Scatter Plot
Box Plot
Violin Plot
(D)
Q.11
What is the primary purpose ofa density plot in EDA?
To visualize the distribution of data
To display relationships between variables
To identify missing values
To calculate summary statistics
(A)
Q.12
In EDA, what is the primary purpose of a pie chart?
To identify missing values
To visualize the distribution of data
To display relationships between variables
To compare multiple categories
(D)
Q.13
Which EDA technique is commonly used to visualize the relationship between two continuous variables through a 2D plot?
Bar Chart
Scatter Plot
Box Plot
Histogram
(B)
Q.14
What does the term "scatter matrix" refer to in the context of EDA?
A matrix of bar charts
A collection of scatter plots
A matrix of correlation coefficients
A matrix of histogram plots
(B)
Q.15
Which EDA technique is used to visualize the relationship between two categorical variables in a contingency table format?
Bar Chart
Box Plot
Scatter Plot
Crosstabulation
(D)
Q.16
What is the primary purpose of a violin plot in EDA?
To identify missing values
To visualize the distribution of data
To display relationships between variables
To compare multiple categories
(B)
Q.17
What is the primary goal of a pair plot (scatter plot matrix) in EDA?
To visualize the distribution of data
To display relationships between variables
To identify missing values
To calculate summary statistics
(B)
Q.18
Which EDA technique is used to visualize the distribution of a single categorical variable?
Bar Chart
Scatter Plot
Воx Plot
Histogram
(A)
Q.19
In EDA, what is the primary purpose of a heat map?
To calculate summary statistics
To visualize the distribution of data
To display relationships between variables
To identify missing values
(C)
Q.20
What does the term "kurtosis" refer to in the context of data distribution analysis in EDA?
The presence of outliers
The symmetry of a data distribution
The spread of a data distribution
The shape of a data distribution
(D)
Q.21
In EDA, what does the term "box"represent in a box plot?
Median
Mode
Range
Standard Deviation
(A)
Q.22
Which EDA technique is used to visualize the distribution of a single continuous variable?
Bar Chart
Box Plot
Histogram
Scatter Plot
(C)
Q.23
What is the primary purpose of a bar chart in EDA?
To identify missing values
To visualize the distribution of data
To display relationships between variables
To compare multiple categories
(D)
Q.24
What is the primary goal of a density plot in EDA?
To calculate summary statistics
To visualize the distribution of data
To display relationships between variables
To identify missing values
(B)
Q.25
Which EDA technique is used to display the distribution of a single variable, especially in cases of categorical data?
Bar Chart
Box Plot
Scatter Plot
Histogram
(D)
Q.26
What does the term "skewness" refer to in the context of data distribution analysis in EDA?
The symmetry of a data distribution
The kurtosis of a data distribution
The spread ofa data distribution
The presence of outliers
(A)
Q.27
Which EDA technique is used to visualize the relationship between a categorical variable and a continuous variable?
Bar Chart
Box Plot
Scatter Plot
Histogram
(B)
Q.28
In EDA, what is the purpose of a Q-Q plot (Quantile-Quantile plot)?
To display time series data
To visualize the distribution of data
To compare two different datasets
To check for normality in data
(D)
Q.29
What type of data visualization is commonly used in EDA to represent the distribution of a categorical variable?
Bar Chart
Scatter Plot
Воx Plot
Histogram
(A)
Q.30
What does the term "outlier" refer to in the context of EDA?
A data point that is missing
A point that falls within the data range
A data point that is part of the main cluster
A data point that falls far from the rest
(D)
Q.31
Which EDA technique is used to visualize the relationship between two continuous variables with a line connecting data points?
Box Plot
Scatter Plot
Histogram
Bar Chart
(B)
Q.32
What is the purpose of a correlation matrix in EDA?
To calculate summary statistics
To visualize the distribution of data
To display relationships between variables
To identify missing values
(C)
Q.33
Which EDA technique is used to identify and visualize outliers in a dataset?
Histogram
Bar Chart
Box Plot
Scatter Plot
(C)
Q.34
In EDA, which measure of central tendency is typically represented by the height of a box in a box plot?
Variance
Mean
median
Mode
(C)
Q.35
What is the primary purpose of a scatter plot in EDA?
To represent time series data
To show the distribution of a single variable
To visualize relationships between variables
To display categorical data
(C)
Q.36
In EDA, what is the term for a graphical representation that displays the distribution of a continuous variable?
Scatter Plot
Pie Chart
Histogram
Bar Chart
(C)
Q.37
Which of the following is NOT a common EDA technique for visualizing data distributions?
Histogram
Box Plot
Scatter Plot
Bar Chart
(D)
Q.38
What is the primary purpose of Exploratory Data Analysis (EDA) in Data Science?
To simplify complex data
To make data more complicated
To visualize data
To discover patterns and insights in data
(D)
Q.39
Which of the following function is used for searching text strings by means of regular expression?
gepexpr
grepd
grepl
all of the mentioned
(C)
Q.40
Which of the following package is used for tidy data?
souryr
tidyr
NumPy
all of the mentioned
(B)
Q.41
Which of the following function is used for loading flat files?
read.table
read.data
read.sheet
none of the mentioned
(A)
Q.42
Which of the following package is used for reading HTML and XML data?
httx
httr
http
all of the mentioned
(B)
Q.43
Which of the following request can be issued from httr package?
DELETE
GET
PUT
All of the mentioned
(D)
Q.44
In data preprocessing, what is the term for the process of handling missing data by filling in the missing values with estimates?
Data Encoding
Data Imputation
Data Normalization
Data Transformation
(B)
Q.45
Which data collection method involves selecting a subset of individuals or elements from a larger population for study?
Experiments
Observational Studies
Surveys
Sampling
(D)
Q.46
What is the purpose of feature engineering in data preprocessing?
To visualize data
To make data more complex
To extract meaningful features
To perform data cleaning
(C)
Q.47
In data preprocessing, what is the term for the process of converting text data into numerical values?
Data Transformation
Data Encoding
Data Tokenization
Data Parsing
(B)
Q.48
Which of the following is NOT a common data preprocessing technique?
Data Visualization
Data Cleaning
Data Encoding
Data Imputation
(A)
Q.49
What is the term for the process of organizing and storing data in a structured format that enables efficient retrieval?
Data Warehousing
Data Integration
Data Transformation
Data Aggregation
(A)
Q.50
What is the primary goal of data preprocessing in the context of machine learning?
To reduce the size of the dataset
To increase data complexity
To prepare data for analysis
To create visualizations of the data
(C)
Q.51
Which data preprocessing step involves checking for and handling duplicate records in a dataset?
Data Encoding
Data Deduplication
Data Aggregation
Data Scaling
(B)
Q.52
What is the term for data that is collected from asingle source at a specific point in time?
Panel Data
Cross-Sectional Data
Time Series Data
Longitudinal Data
(B)
Q.53
What is the purpose of data sampling in data collection?
To remove outliers
To analyze the entire dataset
Тo collect data from various sources
To select a representative subset
(D)
Q.54
Which data collection method involves manipulating one or more variables to observe their effects on other variables?
Interviews
Observational Studies
Experiments
Surveys
(C)
Q.55
In data preprocessing, what is the process of converting data values into a standard format to remove noise and variations?
Data Imputation
Data Scaling
Data Transformation
Data Normalization
(D)
Q.56
What does the acronym "ETL" stand for in the context of data preprocessing and integration?
Estimate, Transform, Load
Extract, Transform, Load
Encrypt, Transmit, Log
Evaluate, Test, Learn
(B)
Q.57
Which data collection method involves the collection of data at regular intervals over a period of time?
Time Series Data Collection
Oservational Studies
Experiments
Surveys
(A)
Q.58
What is the term for the process of reducing the dimensionality of data while retaining its most important features?
Data Normalization
Data Imputation
Data Scaling
Data Reduction
(D)
Q.59
What is the term for the process of handling missing data in a dataset by estimating values based on available data?
Data Encoding
Data Imputation
Data Normalization
Data Transformation
(B)
Q.60
In data preprocessing, what is the term for the process of converting categorical data into binary format?
Data Aggregation
Data Encoding
Data Normalization
Data Imputation
(B)
Q.61
What is the primary goal of data preprocessing in the context of machine learning?
To create visualizations of the data Discover more Ask question feature Discuss
To make the data more complex
To prepare the data for analysis
To reduce the size of the dataset
(C)
Q.62
Which data preprocessing step involves checking for and handling duplicate records in a dataset?
Data Encoding
Data Deduplication
Data Aggregation
Data Scaling
(B)
Q.63
What is the term for the process of selectinga representative subset of a larger dataset for analysis?
Data Cleaning
Data Sampling
Data Integration
Data Transformation
(B)
Q.64
In data collection, what is the term for data that has not been processed or analyzed and is in its original form?
Structured Data
Raw Data
Processed Data
Analytical Data
(B)
Q.65
Which of the following is NOT a common data preprocessing technique?
Data Aggregation
Data Encoding
Data Normalization
Data Imputation
(A)
Q.66
What is the purpose of feature engineering in data preprocessing?
To visualize data
To make data more complex
Тo extract meaningful features
To perform data cleaning
(C)
Q.67
Which data collection method involves gathering data by directly interacting with subjects or participants?
Sampling
Surveys
Observations
Experiments
(D)
Q.68
What is the term for the process of converting data into a structured format suitable for analysis and storage?
Data Cleaning
Data Integration
Data Transformation
Data Wrangling
(C)
Q.69
Which of the following is a common technique for handling outliers in a dataset?
Data Scaling
Data Imputation
Data Transformation
Data Visualization
(A)
Q.70
What type of data collection method involves manipulating one or more variables to observe their effects on other variables?
Interviews
Observations
Surveys
Experiments
(D)
Q.71
In data preprocessing, what is the purpose of data scaling or normalization?
To create new features
To increase data complexity
To standardize data
To remove outliers
(C)
Q.72
Which data collection method involves selecting asample from a larger population and collecting data from the sample only?
Sampling
Experiments
Observational Studies
Surveys
(A)
Q.73
What is the process of converting text data into a numerical format so that it can be used in machine learning algorithms called?
Data Transformation
Data Encoding
Data Tokenization
Data Parsing
(C)
Q.74
Which of the following is a common technique for handling imbalanced data in classification problems?
Data Imputation
Data Augmentation
Data Scaling
Data Encoding
(B)
Q.75
In data preprocessing, what is the term for the identification and removal of duplicate or redundant data?
Data Imputation
Data Deduplication
Data Aggregation
Data Normalization
(B)
Q.76
Which of the following is NOT a common step in data preprocessing?
Data Integration
Data Cleaning
Data Visualization
Data Transformation
(C)
Q.77
What is the process of transforming categorical data into numerical values called?
Data Standardization
Data Encoding
Data Imputation
Data Transformation
(B)
Q.78
Which type of data collection method involves asking questions to gather information from respondents?
Observations
Experiments
Surveys
Interviews
(C)
Q.79
Which of the following is a common technique used to preprocess text data, involving the removal of common words?
Data Stopword Removal
Data Stemming
Data Tokenization
Data Parsing
(A)
Q.80
What is the term for the process of reducing the size of a dataset while retaining its essential characteristics?
Data Cleaning
Data Wrangling
Data Reduction
Data Sampling
(C)
Q.81
Which method of data collection involves systematically observing and recording data without interfering with the subjects?
Observational Studies
Surveys
Interviews
Experiments
(A)
Q.82
What does the acronym "API"stand for in the context of data collection and retrieval?
Analytical Program Interaction
Application Programming Interface
Advanced Protocol Interface
Automated Process Integration
(B)
Q.83
Which of the following is a technique used to handle missing data by filling in the missing values with estimated data?
Data Imputation
Data Normalization
Data Transformation
Data Encoding
(A)
Q.84
What is the process of cleaning and formatting raw data into a usable format called?
Data Integration
Data Visualization
Data Cleaning
Data Extraction
(C)
Q.85
Which of the following is a type of structured data that is organized in rows and columns, similar to a spreadsheet?
XML
CSV
JSON
Unstructured Text Data
(B)
Q.86
In data collection, what is the term for the process of recording data in its original form without any changes?
Data Transformation
Data Integration
Data Aggregation
Raw Data Collection
(D)
Q.87
Which of the following is NOT a common source of data for data collection in Data Science?
Customer Surveys
Social Media
Sensor Data
Print Media
(D)
Q.88
What is the process of gathering data from various sources and storing it for analysis known as?
Data Collection
Data Wrangling
Data Visualization
Data Aggregation
(A)
Q.89
Point out the correct statement?
If equations and parameter are not, they may be inferred with data analysis
If equations are known but the parameters are not, they may be inferred with data analysis
If equations are not known but the parameters are, they may be inferred with data Oanalysis
None of the mentioned
(B)
Q.90
Which of the following uses relatively small amount of data to estimate about bigger population?
Exploratory
Inferential
Causal
None of the mentioned
(B)
Q.91
Which of the following analytical capabilities are provided by information management company?
Content Management
Stream Computing
Information Integration
All of the mentioned
(D)
Q.92
Which of the following is the common goal of statistical modelling?
Summarizing
Inference
Subsetting
None of the mentioned
(B)
Q.93
Which of the following characteristic of big data is relatively more concerned to data science?
Volume
Velocity
Variety
None of the mentioned
(C)
Q.94
Which of the following is the top most important thing in data science?
question
answer
data
None of the mentioned
(A)
Q.95
Point out the correct statement?
Preprocessed data is original source of data
Raw data is original source of data
Raw data is the data obtained after processing steps
None of the mentioned
(B)
Q.96
Which of the following is a good way of performing experiments in data science?
Generalize to the problem
Measure variability
Have Replication
All of the mentioned
(D)
Q.97
Which of the following technique comes under practical machine learning?
Вoosting
Bagging
Forecasting
None of the mentioned
(A)
Q.98
Point out the wrong statement?
Complication approached exist for inferring causation
Randomized studies are not used to identify causation
Causal relationships may not apply to every individual
All of the mentioned
(B)
Q.99
Which of the following relationship are usually identified as average effects?
Causal
Descriptive
Predictive
None of the mentioned
(A)
Q.100
Which of the following command allows you to update the repository?
pop
push
update
one of the mentioned
(B)
Q.101
Which of the following is not a step in data analysis?
Clean the data
Obtain the data
EDA
None of the mentioned
(D)
Q.102
Which of the following is characteristic of Raw Data?
Original version of data
Data is ready for analysis
Easy to use for data analysis
None of the mentioned
(A)
Q.103
Point out the correct statement?
CLI can help you to organize files and folders
You don't need GitHub to use Git
Navigation of directory is possible using CLI
None of the mentioned
(A)
Q.104
Which of the following is characteristic of Processed Data?
All steps should be noted
Data is not ready for analysis
Hard to use for data analysis
None of the mentioned
(A)
Q.105
Which of the following is a revision control system?
NumPy
Git
Slidify
None of the mentioned
(B)
Q.106
Point out the correct statement_____?
CLI can help you to organize files and folders
CLI can help you to organize messages
Navigation of directory is possible using CLI
None of the mentioned
(A)
Q.107
Which of the following is the correct way of creating GitHub repository in to well labelled commits?
Pop another user's repository
Fork another user's repository
Zip another user's repository
None of the mentioned
(B)
Q.108
Which of the following command help us to give message description?
git command -d
git command -m
git command -message
none of the mentioned
(B)
Q.109
Which of the following is one of the key data science skills?
Machine Learning
Statistics
Data Visualization
All of the mentioned
(D)
Q.110
Which of the following systems record changes to a file over time?
Version Control
Record Control
Forecast Control
None of the mentioned
(A)
Q.111
Point out the correct statement______?
Inferential models are useful for discovering new connection
Exploratory analyses are not usually the final way
Inference involves estimating uncertainty
All of the mentioned
(C)
Q.112
Which of the following allows you to find the relationship you didn't about?
Causal
Inferential
Exploratory
None of the mentioned
(C)
Q.113
Which of the following analysis helps out to find the effect of variable change?
Exploratory
Inferential
Causal
None of the mentioned
(C)
Q.114
Which of the following step is performed by data scientist after acquiring the data?
Data Integration
Data Cleansing
Data Replication
All of the mentioned
(B)
Q.115
Which of the following is not a CLI command?
rm
delete
clear
none of the mentioned
(B)
Q.116
Point out the wrong statement_____?
The data growth and social media explosion have changed how we look at the data
The big volume indeed represents Big Data
Big Data is just about lots of data
All of the mentioned Discover more Answer
(C)
Q.117
Which of the following uses data on some object to predict values for other object?
Exploratory
Inferential
Predictive
None of the mentioned
(C)
Q.118
Point out the wrong statement.
Subsetting can be used to select and exclude variables and observations
Merging concerns combining datasets on the same observations to produce a result with more variables
Data visualization is the organization of information according to preset specifications
All of the mentioned
(C)
Q.119
Which of the following is a key characteristic of a hacker?
Not Willing to find answers on their own
Afraid to say they don't know the answer
Willing to find answers on their own
All of the mentioned
(C)
Q.120
Which of the following approach should be used to ask Data Analysis question?
Find out the question which is to be answered
Find only one solution for particular problem
Find out answer from dataset without asking question
None of the mentioned
(A)
Q.121
Which of the following technique is also referred to as Bagging?
Bootstrap subsetting
Bootstrap predicting
Bootstrap aggregating
All of the mentioned
(C)
Q.122
Point out the correct statement?
Descriptions can be generalized without statistical modelling
Descriptive analysis is first kind of data analysis performed
Description and Interpretation are same in descriptive analysis
None of the mentioned
(A)
Q.123
Which of the following approach should be used if you can't fix the variable?
non stratify it
randomize it
generalize it
none of the mentioned
(B)
Q.124
Which of the following focuses on the discovery of (previously) unknown properties on the data?
Big Data
Data mining
Data wrangling
Machine Learning
(B)
Q.125
Which of the following analysis are incredibly hard to infer?
Exploratory
Inferential
Causal
Mechanistic
(D)
Q.126
Point out the wrong statement?
Exploratory models are useful for discovering new connection
Exploratory analyses are usually the final way
Exploratory analysis alone should not be used for predicting
All of the mentioned
(B)
Q.127
How many principles of analytical graphs exist?
3
4
6
None of the mentioned
(C)
Q.128
Point out the correct statement_____?
Correlation does imply causation
Descriptive analysis can be more useful for defining future studies
Inference is commonly the goal of statistical model
None of the mentioned
(A)
Q.129
Which of the following web hosting service use Git control system?
Open Hash
GitHub
Git Bash
None of the mentioned
(B)
Q.130
Which of the following CLI command can also be used to rename files?
mv
rm
rm -r
none of the mentioned
(A)
Q.131
hich of the following command updates tracking for files that are modified?
git add -u
git add.
git add -A
none of the mentioned
(A)
Q.132
Which of the following model is usually a gold standard for data analysis?
Descriptive
Inferential
Causal
All of the mentioned
(C)
Q.133
Point out the correct statement?
Least square problems falls in to three categories
Least square is an estimation tool
Compound least square is one of the category of least square
None of the mentioned
(B)
Q.134
Which of the following is performed by Data Scientist?
Create reproducible code
Define the question
Challenge results
All of the mentioned
(D)
Q.135
Which of the following command is used to give a message description?
git command -d
git command -m
git command -message
none of the mentioned
(B)
Q.136
Point out the wrong statement?
Compound linear regression is not equipped to handle more than one predictor
Simple linear regression is equipped to handle more than one predictor
Linear regression consists of finding the best-fitting straight line through the points
All of the mentioned
(B)
Q.137
Which of the following command line environment is used for interacting with Git?
Git Bash
GitHub
Git Boot
All of the mentioned
(A)
Q.138
Which of the following statement would create branch named as 'example'?
git checkout -c example
git checkout -b example
git check -b example
none of the mentioned
(B)
Q.139
Point out the wrong statement?
GitHub allows you to share repositories with others
You need GitHub to use Git
GitHub allows you to access others repositories
All of the mentioned
(B)
Q.140
Which of the following command allows you to change directory to one level above your parent directory?
cd.
cd
cd..
none of the mentioned
(C)
Q.141
Point out the wrong statement?
There is one and only flag for every command in CLI
Command is the CLI command which does a specific task
Flags are the options given to command for activating particular behaviour
All of the mentioned
(A)
Q.142
Which of the following data mining technique is used to uncover patterns in data?
Data booting
Data bagging
Data merging
Data Dredging
(D)
Q.143
Which of the following analysis is usually modeled by deterministic set of equations?
Causal
Predictive
Mechanistic
All of the mentioned
(C)
Q.144
Which of the following command is used to squash the commits?
squash
rebase
Boot
all of the mentioned
(B)
Q.145
Which of the following is NOT typically considered a part of the Data Science process?
Data Visualization
Data Collection
Data Cleaning
Software Development
(D)
Q.146
What is the primary objective of exploratory data analysis (EDA) in Data Science?
To find patterns
To make predictions
To transform data
To summarize data
(A)
Q.147
What is the primary role of a Data Scientist in a business context?
Developing marketing campaigns
Conducting market research
Leveraging data for insights
Extracting data from databases
(C)
Q.148
Which of the following is a common method for dealing with missing data in a dataset?
Imputing missing values
Dropping missing values
Normalizing the data
Creating new features
(A)
Q.149
Which step in the Data Science process involves visualizing and interpreting the results of data analysis?
Data Cleaning
Data Collection
Data Visualization
Model Building
(C)
Q.150
What does the acronym "SQL" stand for in the context of Data Science?
Statistical Query Language
Structured Query Language
Simplified Query Language
Secure Query Language
(B)
Q.151
Which of the following is a common algorithm used for classification in supervised learning?
Decision Tree
K-Means Clustering
Principal Component Analysis (PCA)
Naive Bayes
(A)
Q.152
What is the process of splitting a dataset into a training set and a test set used for machine learning called?
Data Sampling
Data Partitioning
Data Shuffling
Data Splitting
(A)
Q.153
In Data Science, what is the purpose of data wrangling?
To transform raw data
To create complex models
To remove outliers
To visualize data
(A)
Q.154
Which type of data is represented by categories or labels and cannot be measured numerically?
Categorical Data
Numerical Data
Ordinal Data
Continuous Data
(A)
Q.155
What is the primary objective of data exploration in Data Sciencе?
To find hidden patterns
To build predictive models
To summarize data
To collect data
(A)
Q.156
In Data Science, what is the term for a data point that is missing a value for one or more features?
Anomaly
Outlier
Null Value
Feature
(C)
Q.157
Which statistical measure represents the spread or dispersion of data values in adataset?
Mean
Median
Standard Deviation
Mode
(C)
Q.158
Which of the following best describes the purpose of data sampling in ata Science?
To select a representative subset
To analyze the entire dataset
To calculate data statistics
To visualize data
(A)
Q.159
What is the term for the process of removing or reducing noise and inconsistencies from data?
Data Transformation
Data Integration
Data Aggregation
Data Cleansing
(D)
Q.160
In Data Science, what is the term for the process of reducing the dimensionality of a dataset while preserving information?
Data Cleaning
Dimensionality Reduction
Feature Engineering
Data Transformation
(B)
Q.161
Which of the following is NOT a common data visualization tool or library used in Data Science?
Seaborn
Tableau
Power BI
Excel
(D)
Q.162
What is the process of converting categorical variables into numerical values for machine learning called?
Data Encoding
Feature Extraction
Data Standardization
Label Encoding
(A)
Q.163
Which of the following is NOT a key role in a typical Data Science team?
Data Analyst
Data Engineer
Data Scientist
Database Administrator
(D)
Q.164
What type of data analysis focuses on understanding the relationships and patterns within a dataset?
Predictive Analysis
Descriptive Analysis
Inferential Analysis
Diagnostic Analysis
(B)
Q.165
Which of the following is a common technique used to handle imbalanced datasets in classification problems?
Downsampling
Upsampling
Feature Engineering
Data Wrangling
(B)
Q.166
Which step in the Data Science process involves assessing the quality of collected data?
Data Cleaning
Data Collection
Data Validation
Data Visualization
(C)
Q.167
In data Science,what is the primary purpose of data visulization?
To complicate data
To make data more confusing
To obscure patterns in data
To help communicate insights from data
(D)
Q.168
What is the term for the process of cleaning and organizing data into a structured format suitable for analysis?
Data Extraction
Data Transformation
Data Visualization
Data Aggregation
(B)
Q.169
Which library in Python is commonly used for data manipulation and analysis in Data Science?
Matplotlib
Pandas
Scikit-Learn
TensorFlow
(B)
Q.170
Which of the following is an example of an unsupervised learning algorithm used in clustering data?
Decision Trees
Linear Regression
K-Мeans Clustering
Logistic Regression
(C)
Q.171
What is the term for a machine learning algorithm that learns from historical data to make predictions about the future?
Clustering
Regression
Classification
Supervised Learning
(D)
Q.172
In Data Science, what is the purpose of feature engineering?
To model data features
To extract features from data
To visualize data features
To clean data features
(B)
Q.173
Which statistical measure represents the middle value of a dataset when it is sorted in ascending order?
Mean
Median
Standard Deviation
Mode
(B)
Q.174
What is the process of extracting patterns and information from data called?
Data Visualization
Data Wrangling
Data Engineering
Data Mining
(D)
Q.175
Which step in the Data Science process involves building and training predictive models?
Data Visualization
Data Collection
Data Cleaning
Model Building
(D)
Q.176
What is the primary purpose of data visualization in Data Science?
To store data
To make data more complicated
To simplify complex data
To increase data complexity
(C)
Q.177
Which of the following is a technique used to handle missing data in a dataset?
Data Imputation
Data Augmentation
Data Transformation
Data Normalization
(A)
Q.178
Which of the following is NOT a common data format used in Data Science projects?
XML
JSON
CSV
HTML
(D)
Q.179
What is the primary focus of Data Science?
Data Visualization
Data Cleaning
Data Analysis
Data Storage
(C)
Q.180
In Data Science, what is the term for a dataset that contains both input features and output labels?
Training Data
Test Data
Unlabeled Data
Validation Data
(A)
Q.181
Which step in the Data Science process involves selecting the appropriate model and algorithm for analysis?
Data Visualization
Data Cleaning
Data Collection
Model Building
(D)
Q.182
Which of the following is NOT a key skill required for a Data Scientist?
Storytelling
Data Visualization
Database Administration
Machine Learning
(C)
Q.183
What does the acronym "EDA" stand for in Data Science?
Effective Data Algorithms
Exploratory Data Analysis
Extracted Data Aqgregation
Efficient Data Assessment
(B)
Q.184
Which technology is often used to process and analyze large-scale data sets in Data Science?
SQL
Hadoop
Python
HTML
(B)
Q.185
Which of the following is NOT a type of machine learning algorithm commonly used in Data Science?
K-Means Clustering
Linear Regression
Decision Trees
Object-Oriented Programming
(D)
Q.186
What is the term for a data point that falls far from the rest of the data in a dataset?
Median
Outlier
Mean
Variance
(B)
Q.187
Which step in the Data Science process involves understanding and preparing the data for analysis?
Data Visualization
Data Collection
Data Cleaning
Model Building
(C)
Q.188
Which programming language is commonly used for Data Science tasks?
Python
Java
C++
Java Script
(A)
Q.189
What is the primary goal of Data Science?
Data Cleaning
Data Visualization
Predictive Analytics
Extracting Data from APIs
(C)
