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Data Handling - 2 Class 6 Worksheet Maths

Q1: The following pictograph shows the number of pet animals sold in a month –
Each symbol  = 5 pets

Data Handling - 2 Class 6 Worksheet Maths

(i) How many more Cats were sold as compared to Sheep ?
(a) 25
(b) 10
(c)  20

(ii) How many Parrots were sold in a month?
(a) 16
(b) 15
(c) 10

(iii) Which pet was sold the most ?
(a) Parrot
(b) Rabbit
(c) Dog

(iv) How many Dogs were sold in a month ?
(a) 35
(b) 55
(c) 30

(v) Which pet was sold the least ?
(a) Dog
(b) Cat
(c) Sheep

Q2: Given below is a bar graph showing the number of A.C sold in 5 months –
Data Handling - 2 Class 6 Worksheet Maths

(i) How many A.C were sold in the month of May ?
(a) 60
(b) 40
(c) 30

(ii) In which month minimum number of A.C were sold ?
(a) April
(b) March
(c) June

(iii) How many more A.C were sold in the month June than in July?
(a) 60
(b) 30
(c) 40

(iv) How many A.C were sold in the month of April ?
(a) 70
(b) 40
(c) 50

(v) In which month maximum number of A.C were sold ?
(a) June
(b) May
(c) July


You can find Worksheets Solutions here: Worksheet Solutions: Data Handling - 2

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FAQs on Data Handling - 2 Class 6 Worksheet Maths

1. What is data handling?
Ans. Data handling refers to the process of managing and manipulating data to extract meaningful information from it. It involves tasks like collecting, organizing, storing, and analyzing data to make informed decisions.
2. Why is data handling important?
Ans. Data handling is important because it allows us to make sense of the vast amount of information available to us. By organizing and analyzing data, we can identify patterns, trends, and insights that can help in decision-making, problem-solving, and planning.
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 information from various sources. Data storage involves storing the collected data in a structured manner. Data cleaning is the process of removing errors or inconsistencies from the data. Data analysis involves examining the data to identify patterns or trends. Data visualization is the presentation of data using visual elements like charts or graphs.
4. What are some common challenges in data handling?
Ans. Some common challenges in data handling include data quality issues, data security concerns, data privacy concerns, data integration difficulties, and data overload. Data quality issues refer to errors or inconsistencies in the collected data. Data security concerns involve protecting the data from unauthorized access or breaches. Data privacy concerns involve ensuring that personal or sensitive information is handled appropriately. Data integration difficulties arise when combining data from different sources. Data overload refers to the overwhelming amount of data that can make analysis and decision-making challenging.
5. How can data handling benefit businesses?
Ans. Data handling can benefit businesses in various ways. It can provide insights into customer behavior, preferences, and needs, allowing businesses to tailor their products or services accordingly. It can also help in identifying market trends, optimizing operations, and improving overall efficiency. Additionally, data handling can facilitate data-driven decision-making, enabling businesses to make informed choices based on evidence and analysis rather than intuition alone.
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