CBSE Class 10 AI Unit 4 MCQs with Answers & Explanations (2026–27) | Statistical Data

Correct Answer: B. Data Science

Explanation: Data Science combines Mathematics, Statistics, Computer Science, and Machine Learning to collect, analyze, and interpret data for solving real-world problems and making informed decisions.

Why other options are incorrect:

• A. Computer Vision focuses on enabling machines to interpret images and videos.
• C. Natural Language Processing deals with understanding human language.
• D. Hardware Engineering involves designing physical computer systems.

Correct Answer: A. Fractions of a second

Explanation: Search engines such as Google use Data Science and Machine Learning algorithms to analyze billions of web pages and display the most relevant results within fractions of a second.

Why other options are incorrect:

• B. Modern search engines are much faster.
• C. Search results are delivered instantly, not after days.
• D. Users receive search results, not binary code.

Correct Answer: C. Past behavior

Explanation: Data Science analyzes a user's browsing history, searches, purchases, and interests to display advertisements that are more relevant to that user.

Why other options are incorrect:

• A. Eye color is unrelated to online advertising.
• B. Future intentions cannot be known with certainty.
• D. Advertisements are generally personalized rather than random.

Correct Answer: D. Make AI accessible to the general public

Explanation: No-Code AI platforms allow users without programming knowledge to build AI applications using simple graphical interfaces and drag-and-drop components.

Why other options are incorrect:

• A. No-Code platforms require little or no programming knowledge.
• B. They are specifically designed for non-technical users.
• C. Their objective is ease of development, not higher cost.

Correct Answer: A. Traditional manual programming

Explanation: High Code development requires programmers to write software manually using programming languages such as Java, Python, or C++.

Why other options are incorrect:

• B. Drag-and-drop interfaces are features of Low-Code or No-Code platforms.
• C. No-Code development requires little or no programming.
• D. High Code is related to software development, not hardware.

Correct Answer: B. Low Code

Explanation: Low-Code platforms provide ready-made components and visual interfaces but still require developers to write some custom code.

Why other options are incorrect:

• A. High Code depends almost entirely on manual programming.
• C. No-Code platforms generally require no coding.
• D. "Zero Code" is not a standard software development approach.

Correct Answer: C. Significantly faster

Explanation: No-Code platforms accelerate application development by providing pre-built components, allowing users to create applications much faster than traditional coding.

Why other options are incorrect:

• A. No-Code development is designed to reduce development time.
• B. It is usually faster than traditional coding.
• D. No-Code platforms can also be used for many business applications.

Correct Answer: A. High Code

Explanation: High Code development requires experienced programmers to write, test, debug, and maintain software applications manually.

Why other options are incorrect:

• B. No-Code minimizes dependence on programmers.
• C. Low-Code reduces coding effort through visual tools.
• D. Drag-and-drop is a feature, not a separate development approach.

Correct Answer: D. Build applications easily without programming

Explanation: Drag-and-drop interfaces allow users to create workflows and applications visually, making software development much simpler.

Why other options are incorrect:

• A. Users do not write binary code.
• B. Hardware design is unrelated to No-Code development.
• C. The feature is not limited to database entry.

Correct Answer: C. No-Code Machine Learning Platform

Explanation: Orange is an open-source, No-Code data mining and machine learning platform where users build AI workflows using drag-and-drop widgets.

Why other options are incorrect:

• A. Orange is software, not a hardware tool.
• B. It does not require extensive programming.
• D. Orange is designed as a visual AI workflow platform rather than a traditional programming environment.

Correct Answer: B. Limited flexibility

Explanation: No-Code platforms are easy to use but generally offer less flexibility and customization than traditional High-Code development.

Why other options are incorrect:

• A. No-Code platforms are generally cost-effective.
• C. They are designed for users with little or no programming knowledge.
• D. No-Code platforms are known for faster development and deployment.

Correct Answer: A. Predict food prices

Explanation: Kayla used AI to predict future prices of meat and vegetables so that the zoo could manage its budget effectively.

Why other options are incorrect:

• B. AI was not used for cleaning activities.
• C. Visitor counting was not the objective.
• D. Website design was unrelated to the case study.

Correct Answer: C. It enables non-technical people to build AI solutions.

Explanation: No-Code AI empowers teachers, doctors, business owners, and other non-programmers to create AI applications without writing code.

Why other options are incorrect:

• A. Programming knowledge is not essential.
• B. It is accessible to everyone.
• D. It is much easier than traditional programming.

Correct Answer: D. Java and C#

Explanation: Traditional High-Code software development relies on programming languages such as Java, Python, C++, and C#.

Why other options are incorrect:

• A. These are spoken languages.
• B. Programmers do not directly develop software in binary.
• C. HTML and CSS are mainly used for web page structure and styling.

Correct Answer: B. Population

Explanation: Population refers to the entire set of observations or data available for a study or experiment.

Why other options are incorrect:

• A. A Sample is only a part of the Population.
• C. Distribution describes how data values are spread.
• D. Segment is not the correct statistical term.

Correct Answer: B. Because studying the entire Population is often difficult and time-consuming

Explanation: When the Population is very large, collecting data from every member is expensive and impractical. Therefore, a representative Sample is used.

Why other options are incorrect:

• A. Data is still collected from a Sample.
• C. Sampling simplifies analysis.
• D. Sampling has no effect on making the Mean zero.

Correct Answer: C. Median

Explanation: The Median is the middle value after arranging all observations in ascending or descending order.

Why other options are incorrect:

• A. Mean is the arithmetic average.
• B. Mode is the most frequently occurring value.
• D. Variance measures the spread of data.

Correct Answer: A. The most frequently occurring value

Explanation: Mode is the value that appears most often in a dataset.

Why other options are incorrect:

• B. This defines Mean.
• C. This defines Median.
• D. This represents the Range.

Correct Answer: B. Average

Explanation: Mean is calculated by adding all observations and dividing the total by the number of observations.

Why other options are incorrect:

• A. Middle Value refers to the Median.
• C. Mean is not necessarily the highest value.
• D. Frequency counts occurrences of values.

Correct Answer: B. Distributions

Explanation: A Distribution shows how data values are spread and how often each value appears.

Why other options are incorrect:

• A. Samples are subsets of a Population.
• C. Probability measures the likelihood of events.
• D. Outliers are unusually distant data points.

Correct Answer: C. 4

Explanation:

Mean = (1 + 4 + 5 + 6 + 4) ÷ 5

= 20 ÷ 5 = 4

The Mean is the arithmetic average of all observations.

Why other options are incorrect:

• A. Incorrect calculation.
• B. This is one of the values in the dataset, not the Mean.
• D. This is the sum of all observations.

Correct Answer: B. 4

Explanation: The Mode is the value that occurs most frequently. In this dataset, the number 4 appears twice, while all other values appear only once.

Why other options are incorrect:

• A. Appears only once.
• C. Appears only once.
• D. Appears only once.

Correct Answer: D. A symmetrical distribution with most values around a central peak

Explanation: A Normal Distribution has a bell-shaped curve where most values are concentrated around the center, and both sides are nearly symmetrical.

Why other options are incorrect:

• A. A Normal Distribution is symmetrical.
• B. Outliers alone do not define a Normal Distribution.
• C. Every Normal Distribution has a Mean.

Correct Answer: C. Values that are much larger or smaller than the rest

Explanation: Extremely high or low values pull the distribution toward one side, making it skewed instead of symmetrical.

Why other options are incorrect:

• A. Identical values do not create skewness.
• B. The number of observations does not determine skewness.
• D. Numerical data is required to study distributions.

Correct Answer: B. Likelihood of an event occurring

Explanation: Probability measures how likely it is that a particular event will occur. Its value ranges from 0 (impossible) to 1 (certain).

Why other options are incorrect:

• A. This defines the Median.
• C. This relates to Variance or Standard Deviation.
• D. This refers to the size of the dataset.

Correct Answer: A. Variance

Explanation: Variance measures how much the data values differ from the Mean. A higher Variance indicates that the data is more spread out.

Why other options are incorrect:

• B. Frequency counts occurrences.
• C. Median identifies the middle value.
• D. Mode identifies the most frequent value.

Correct Answer: B. Standard Deviation

Explanation: Standard Deviation measures the average spread of data values around the Mean. A smaller value indicates that the data points are closer to the Mean.

Why other options are incorrect:

• A. An Outlier is a single unusual value.
• C. Mode measures frequency.
• D. Frequency counts occurrences.

Correct Answer: A. Outlier

Explanation: An Outlier is an unusually high or low value that differs significantly from the rest of the dataset.

Why other options are incorrect:

• B. "Inlier" is not the correct statistical term here.
• C. Average refers to the Mean.
• D. Median is the middle value.

Correct Answer: C. Analysis ToolPak

Explanation: The Analysis ToolPak is an Excel Add-in that provides tools for regression, descriptive statistics, and other advanced data analysis tasks.

Why other options are incorrect:

• A. Solver is mainly used for optimization problems.
• B. AI Pak is not an Excel Add-in.
• D. Data Miner is not the required Excel tool.

Correct Answer: B. Scatter Plot

Explanation: A Scatter Plot displays the relationship between two numerical variables, making it ideal for regression analysis such as Speed vs. Distance.

Why other options are incorrect:

• A. Pie Charts show proportions.
• C. Bar Charts compare categories.
• D. Radar Charts compare multiple variables.

Correct Answer: B. y = mx + c

Explanation: The equation y = mx + c represents a straight line used in Linear Regression, where m is the slope and c is the y-intercept.

Why other options are incorrect:

• A. This is not the standard regression equation.
• C. This is not a linear equation.
• D. This is mathematically incorrect.

Correct Answer: D. Canvas

Explanation: The Canvas is the main working area in Orange where users drag and drop widgets to create machine learning workflows.

Why other options are incorrect:

• A. The Palette only contains available widgets.
• B. Dashboard is not the working area in Orange.
• C. "Board" is not the correct term.

Correct Answer: B. Modelling

Explanation: The Modelling category contains machine learning algorithms such as Decision Trees, Logistic Regression, Random Forest, and k-Means.

Why other options are incorrect:

• A. Visualization widgets display graphs and charts.
• C. Data Loading widgets import datasets.
• D. Evaluation widgets assess model performance.

Correct Answer: B. Data Table

Explanation: The Data Table widget allows users to view and inspect datasets in rows and columns.

Why other options are incorrect:

• A. Scatter Plot creates graphs.
• C. File widget loads data.
• D. Python Script executes custom Python code.

Correct Answer: A. File Widget

Explanation: The File widget is the starting point of most Orange workflows and is used to import datasets from local storage or online sources.

Why other options are incorrect:

• B. Data Sampler creates subsets of data.
• C. Test & Score evaluates trained models.
• D. Heat Map visualizes data.

Correct Answer: B. Test & Score

Explanation: The Test & Score widget compares machine learning models and displays performance measures such as Accuracy, Precision, Recall, and AUC.

Why other options are incorrect:

• A. Data Table only displays records.
• C. URL is not an evaluation widget.
• D. Scatter Plot is used for visualization.

Correct Answer: C. Species of penguins

Explanation: The Palmer Penguins dataset is commonly used to build AI models that classify penguins into different species based on their physical characteristics.

Why other options are incorrect:

• A. Weight is only one feature.
• B. Penguins do not fly.
• D. Population prediction was not the objective.

Correct Answer: A. Bill Length (Culmen Length)

Explanation: Bill Length (also called Culmen Length), Bill Depth, Flipper Length, and Body Mass are important features used in the Palmer Penguins dataset.

Why other options are incorrect:

• B. Beak Color is not part of the dataset.
• C. Number of Eggs is not included.
• D. Swimming Depth is not one of the measured features.

Correct Answer: B. Data Acquisition

Explanation: Data Acquisition is the process of collecting or importing data before it is cleaned, explored, and used to build AI models.

Why other options are incorrect:

• A. Modelling comes after data preparation.
• C. Evaluation is performed after training the model.
• D. Deployment occurs after successful evaluation.

Correct Answer: C. Data Exploration

Explanation: During Data Exploration, data is cleaned, unnecessary columns are removed, missing values are handled, and the dataset is prepared for modelling.

Why other options are incorrect:

• A. Problem Scoping identifies the problem.
• B. Evaluation measures model performance.
• D. Modelling is performed after data preparation.

Correct Answer: A. Visualization Widgets

Explanation: Visualization widgets such as Scatter Plot, Box Plot, Heat Map, and Bar Chart help users understand patterns and relationships in data through graphical representations.

Why other options are incorrect:

• B. Modelling widgets are used to train AI models.
• C. Evaluation widgets assess model performance.
• D. Data Loading widgets import datasets.

Correct Answer: C. Unsupervised Clustering

Explanation: k-Means is an Unsupervised Learning algorithm that groups similar data points into clusters without using labeled data.

Why other options are incorrect:

• A. Linear Regression predicts numerical values.
• B. Classification requires labeled data.
• D. File widgets are used to load datasets.

Correct Answer: D. Independent Events

Explanation: Independent events are those in which the occurrence of one event does not affect the probability of another event occurring.

Why other options are incorrect:

• A. Dependent events influence each other's outcomes.
• B. Skewness relates to data distribution, not probability events.
• C. "Normal Events" is not a statistical term.

Correct Answer: B. Classification Model

Explanation: The Coral Bleaching example demonstrates how AI can classify coral reefs into different categories based on collected data.

Why other options are incorrect:

• A. Regression predicts continuous numerical values.
• C. Clustering groups unlabeled data.
• D. It is an AI application, not hardware.

Correct Answer: C. To the left of the peak

Explanation: In a Left-Skewed Distribution, a few extremely small values pull the Mean toward the left side of the graph.

Why other options are incorrect:

• A. This occurs in a Right-Skewed Distribution.
• B. Only a perfectly Normal Distribution has the Mean at the center.
• D. The Mean and Mode are usually different in skewed distributions.

Correct Answer: B. The goodness of fit of the regression line

Explanation: The R² value shows how well the regression line explains the variation in the data. A value closer to 1 indicates a better fit.

Why other options are incorrect:

• A. R² is not an average.
• C. It does not represent the dataset size.
• D. It is not an error measurement.

Correct Answer: B. Create a subset of data

Explanation: The Data Sampler widget selects a representative portion of a dataset, which is useful for testing and experimentation.

Why other options are incorrect:

• A. The File widget imports datasets.
• C. Neural Networks are created using modelling widgets.
• D. Deployment is outside the scope of this widget.

Correct Answer: A. Grams (g)

Explanation: The Palmer Penguins dataset records Body Mass in grams (g), represented by the attribute body_mass_g.

Why other options are incorrect:

• B. Kilograms are not used in the dataset.
• C. Pounds are not used.
• D. Ounces are not used.

Correct Answer: C. Evaluation Widgets

Explanation: Evaluation widgets compare machine learning models and display performance measures such as Accuracy, Precision, Recall, F1 Score, and ROC analysis.

Why other options are incorrect:

• A. Modelling widgets create models.
• B. Data Loading widgets import data.
• D. Visualization widgets display charts and graphs.

Correct Answer: B. Data analysis, visualization, and machine learning

Explanation: Orange is an open-source visual programming tool used for data mining, data visualization, machine learning, and interactive data analysis without extensive coding.

Why other options are incorrect:

• A. Orange focuses on visual workflows rather than manual coding.
• C. It is not used for hardware development.
• D. Although it can analyze data from databases, its purpose is much broader than SQL management.