Class 10 Computer Science — Chapter 5: Data Science

Board: Punjab Board

Exercise Solutions

Multiple Choice Questions (MCQs)

1. What is the first step in the Data Science Life Cycle (DSLC)?

(a) Collecting Data
(b) Visualizing Data
(c) Understanding the Problem
(d) Analyzing the Data

Correct Answer: (c) Understanding the Problem

2. Which method is best for collecting opinions from many students?

(a) IoT Devices
(b) Survey
(c) Web Scraping
(d) Uploading Data

Correct Answer: (b) Survey

3. What is “bias” in data?

(a) Very large data size
(b) Unfair or one-sided data
(c) Well-cleaned data
(d) High-speed data

Correct Answer: (b) Unfair or one-sided data

4. Which tool is ideal for beginners to create charts?

(a) Tableau
(b) Python
(c) Google Sheets
(d) Hadoop

Correct Answer: (c) Google Sheets

5. A relational database stores information in the form of ______.

(a) Slides
(b) Tables
(c) Blocks
(d) Layers

Correct Answer: (b) Tables

6. Which of the following charts is best for comparing groups?

(a) Pie Chart
(b) Bar Chart
(c) Line Chart
(d) Area Chart

Correct Answer: (b) Bar Chart

7. What is the main goal of analyzing data?

(a) Delete old data
(b) Decorate data
(c) Find patterns and make decisions
(d) Connect data to the internet

Correct Answer: (c) Find patterns and make decisions

8. Which of the following tools is an advanced data visualization platform?

(a) MS Paint
(b) Google Data Studio
(c) Notepad
(d) WhatsApp

Correct Answer: (b) Google Data Studio (now Looker Studio)

9. What should be done before storing data?

(a) Add animations
(b) Clean and validate it
(c) Encrypt it
(d) Translate it

Correct Answer: (b) Clean and validate it

10. Which one is an example of a data source?

(a) YouTube
(b) Survey form
(c) Whiteboard
(d) Slide show

Correct Answer: (b) Survey form

Short Answer Questions

1. What is the importance of understanding a problem before collecting data?

Answer:

Understanding the problem first ensures that data collection is focused, relevant, and efficient. It prevents wasting time and resources on unnecessary data that does not address the main objective.

2. Name any two methods of collecting data and give one example of each.

Answer:

1. Surveys/Questionnaires: Collecting feedback directly from individuals.
   Example: A Google Form sent to students asking about their preferred subjects.

2. Web Scraping: Automatically extracting data from websites using software.
   Example: Collecting daily product prices from an e-commerce website.

3. What do we mean by cleaning data?

Answer:

Data cleaning involves identifying and fixing errors, duplicate entries, missing values, incorrect formatting, and irrelevant records within a dataset to ensure accuracy and consistency before analysis.

4. Why is it important to validate data before using it?

Answer:

Data validation ensures that collected information is accurate, complete, logically consistent, and correctly formatted. It helps prevent incorrect insights and poor decisions during analysis.

5. What is the purpose of visualizing data using charts?

Answer:

Data visualization presents complex numerical data in graphical forms, such as bar charts and pie charts. It makes it easier to identify trends, patterns, outliers, and insights quickly.

6. How does bias in data affect results?

Answer:

Bias in data introduces unfairness or a systematic preference toward a particular group or outcome. It can lead to inaccurate conclusions, incorrect predictions, and discriminatory decisions.

7. Write two steps you will follow to clean a messy survey.

Answer:

1. Remove Duplicates: Identify and delete duplicate responses submitted by the same participant.

2. Handle Missing Values: Fill in missing values where appropriate or remove incomplete survey records when necessary.

8. Name any two tools used for creating charts.

Answer:

1. Google Sheets or Microsoft Excel

2. Tableau or Google Data Studio (Looker Studio)

Long Answer Questions

1. Explain the six steps of the Data Science Life Cycle (DSLC) with one line each.

Answer:

1. Problem Understanding: Clearly define the main objectives and questions that need to be answered.

2. Data Collection: Gather relevant data from sources such as surveys, sensors, and databases.

3. Data Cleaning and Preparation: Fix missing values, correct formatting errors, and remove duplicate entries.

4. Data Exploration and Analysis: Analyze the cleaned dataset to discover trends, correlations, and patterns.

5. Data Visualization: Create charts and visual dashboards to present findings clearly.

6. Deployment and Decision Making: Use the insights obtained to solve problems and guide decisions.

2. Give a detailed comparison between Bar Chart, Pie Chart, and Line Chart with examples.

Answer:

1. Bar Chart

Description: A bar chart uses rectangular bars whose lengths or heights represent quantities in different categories. It is best for comparing independent groups or categories.

Example: Comparing the number of students enrolled in different school clubs, such as the Science Club, Sports Club, and Art Club.

2. Pie Chart

Description: A pie chart is a circular graph divided into slices. Each slice represents a proportion or percentage of the whole.

Example: Showing the percentage of a monthly student budget spent on food, transport, books, and entertainment.

3. Line Chart

Description: A line chart connects data points with straight line segments. It is best for showing trends and changes over time.

Example: Tracking a student’s test scores across monthly examinations throughout an academic year.

3. Differentiate between DBMS and SQL.

Answer:

4. Write an SQL query to get all the data of a student whose roll_number is 15 from the student table.

Answer:

SELECT *
FROM student
WHERE roll_number = 15;

Explanation:

• SELECT *: Retrieves all columns from the table.

• FROM student: Specifies the table named student.

• WHERE roll_number = 15: Filters the records to return the student whose roll number is 15.

Notes by Sir Dilawar

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