Class 1 Exam > Class 1 Notes > Mathematics for Class 1 > Worksheet: Data Handling - 1
Data Handling - 1 Class 1 Worksheet Maths Chapter 9
Q1: There are some numbers in the box.
Sort out the numbers in the given table.
Q2: Roshni is playing with her friends in the park. She saw 3 ducks, 2 dogs, 4 birds, 1 tortoise and 2 squirrels.
Colour one box for one animal to show number of animals of each type. One is done for you.
Do you agree with the following? Write ‘Yes’ or ‘No’ in the blanks.
(a) Roshni saw more ducks than dogs. _________
(b) Number of dogs were the same as the number of squirrels. _________
(c) She saw total 12 animals in the park. _________
Q3: Murli bought an item for ₹ 2. He gave a ₹ 50 note to the shopkeeper and got back ₹ 38 in the form of some coins as shown below. Sort the coins in the table given below.
Q4: Look at the following shapes. Sort them by their shades and answer the following questions.
(a) How many 
? _________
(b) How many 
? _________
(c) How many 
? _________
Q5: The class teacher wrote the favourite games of 12 students.
Draw one 
for each game in the blank chart given below. 
(a) Which game is the most popular amongst the 12 students? _______
(b) How many students like Ludo and Tic-Tak-Toe altogether? _______
Q6: Colour as many boxes as the number of flowers you see in the picture. Also, write how many flowers of each type in the last column.
Q7: Which of the following are correct?
(a) Sorting helps in answering required questions.
(b) Sorting is only for fun and has no use in our real-life.
(c) Sorting helps in comparing things.
Q8: Tick (✔) the correct statement.
(a) Sorting means grouping like objects together.
(b) Sorting means grouping unlike objects.
The document Data Handling - 1 Class 1 Worksheet Maths Chapter 9 is a part of the Class 1 Course Mathematics for Class 1.
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FAQs on Data Handling - 1 Class 1 Worksheet Maths Chapter 9
| 1. What is data handling? |  |
Ans. Data handling refers to the process of organizing, analyzing, and interpreting data to extract meaningful insights and make informed decisions. It involves collecting, storing, retrieving, and manipulating data to understand patterns, trends, and relationships within the data.
| 2. Why is data handling important? | |
Ans. Data handling is important because it allows us to make sense of the vast amounts of data that are generated in various fields. By organizing and analyzing data, we can identify patterns, trends, and correlations that can help us solve problems, make predictions, and improve decision-making processes.
| 3. What are the different methods of data handling? | |
Ans. There are several methods of data handling, including data collection, data storage, data cleaning, data analysis, and data visualization. Data collection involves gathering data from various sources, while data storage involves storing the collected data in databases or other storage systems. Data cleaning involves removing errors and inconsistencies from the data, and data analysis involves applying statistical and mathematical techniques to extract insights from the data. Data visualization involves presenting the analyzed data in a visual format, such as charts or graphs.
| 4. What are the challenges in data handling? | |
Ans. Data handling can be challenging due to various factors. Some common challenges include data quality issues, such as missing or incorrect data, data privacy and security concerns, managing large volumes of data, and ensuring data consistency and integrity. Additionally, data handling may require specialized skills and tools, and the complexity of data handling processes can sometimes make it difficult to obtain accurate and reliable results.
| 5. What are the benefits of effective data handling? | |
Ans. Effective data handling can bring several benefits. It can help in making better decisions by providing insights and evidence-based information. It can also improve efficiency by automating manual processes and reducing errors. Data handling can support innovation and discovery by uncovering hidden patterns and relationships in the data. Furthermore, it can enhance customer experience by personalizing products and services based on data analysis. Overall, effective data handling can lead to improved outcomes, increased competitiveness, and better understanding of complex phenomena.
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Nov 21, 2024 Last updated |
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