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Data Handling Class 7 Worksheet Maths Chapter 4

Q.1. State true of false.
(i) A data set may have more than one mode.
(ii) The data set 4, 8, 11, 7, 5, 0 has the mode 0.
(iii) The median can be value which is not equal to any of the observation.
(v) Mean of the observations can be lesser than each of the observations.
(vi) Mean of a data set is the value which divides the value into two equal parts.
(vii) The value of median changes if the value in a data set are arranged in ascending order instead of descending order.
(ix) Mean of the data is always from the given data.
(x) Mode of the data is always from the given data.

Q.2. A batsman scored the following number of runs in six innings:
36, 35, 50, 46, 60, 55
Calculate the mean runs scored by him in an inning

Q.3. Fill in the blanks:
(i) The difference between the highest and lowest values of observations in a set of data is called the_________
(ii) The representation of numbers using bars of uniform width, the length of the bars depicting the frequency is called the_________
(iii) When the raw data is arranged in ascending or descending order, it forms an_________
(vi) The probability of getting 1 in tossing of coin is_________

Q.4. The mean of 5 numbers is 25. If the four numbers 16, 26, 31, 32. Find the fifth numbers.

Q.5. Find the mode of the following data:
24, 26, 23, 26, 22, 25, 26, 28

Q.6. Find the median of the following data:
8, 6, 10, 12, 14

Q.7. A fair die is rolled, find the probability of getting a prime number.

Q.8. Find the mean of the first 5 multiples of 3.

Q.9. Find the mean and median of first five prime numbers.

Q.10. A bag contains 5 white and 9 red balls. One ball is drawn at random from the bag. Find the probability of getting
(a) a white ball
(b) a red ball

Q.11. Find the range of the following data:
21, 16, 30, 15, 16, 18, 10, 24, 26, 20

Q.12. Find the average of the numbers 8, 13, 15.

Q.13. Find the median of the following data:
20, 14, 6, 25, 18, 13, 19, 10, 9, 12

Q.14. The following bar graph shows the number of books sold by a publisher during the five consecutive years. Read the bar graph and answer the following questions:
(i) About how many books were sold in 2008, 2009 and 2012 years?
(ii) In which years were 575 books were sold?
(iii) In which years were the minimum number of books sold?
Data Handling Class 7 Worksheet Maths Chapter 4

Q.15. The marks obtained (out of 10) by 80 students in a class test are given below:
Data Handling Class 7 Worksheet Maths Chapter 4Find the mode of the above data.


You can find Worksheets Solutions here: Worksheet Solution: Data Handling 

The document Data Handling Class 7 Worksheet Maths Chapter 4 is a part of the Class 7 Course Mathematics (Maths) Class 7.
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FAQs on Data Handling Class 7 Worksheet Maths Chapter 4

1. What is data handling in mathematics?
Ans.Data handling in mathematics refers to the process of collecting, organizing, and interpreting data to make sense of it. It involves using various tools and methods, such as charts, graphs, and tables, to represent data visually and analyze it effectively.
2. Why is data handling important in everyday life?
Ans.Data handling is important in everyday life because it helps us make informed decisions based on the information we gather. Whether it's managing finances, analyzing survey results, or understanding trends, data handling skills enable us to draw conclusions and solve problems.
3. What are the different types of data in data handling?
Ans.The different types of data in data handling include qualitative data, which describes characteristics or qualities (like colors or names), and quantitative data, which involves numerical values that can be measured (like height or age). Both types are essential for comprehensive data analysis.
4. How can I represent data visually?
Ans.Data can be represented visually using various methods such as bar graphs, pie charts, line graphs, and histograms. These visual representations make it easier to understand patterns, trends, and comparisons within the data.
5. What are some common mistakes to avoid in data handling?
Ans.Common mistakes to avoid in data handling include misrepresenting data, such as using misleading scales on graphs, failing to label axes clearly, and ignoring outliers that can skew results. It's also important to ensure data is collected consistently and accurately.
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