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PPT: Data Handling

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 Page 1


Data 
Handling
Page 2


Data 
Handling
Topics to be Covered 
1.Introduction
2.Organising Data by using tally marks
3.Pictographs
4.Interpretation of a Pictograph
5.Drawing a Pictograph
6.A bar graph 
7.Interpretation of a bar graph
8.Drawing a bar graph
DATA HANDLING
Page 3


Data 
Handling
Topics to be Covered 
1.Introduction
2.Organising Data by using tally marks
3.Pictographs
4.Interpretation of a Pictograph
5.Drawing a Pictograph
6.A bar graph 
7.Interpretation of a bar graph
8.Drawing a bar graph
DATA HANDLING
Data is a collection of numbers gathered to give some 
information.
For Example: 
?Record the attendance of students in  a class every day.
?Marks obtained by a student after every test or examination.
?Age of all students of your class.
?Choice of sweets or fruits of the students of class 6
th
.
?Size of shoes of students in class 6
th
.
?Marks obtained by all the students of class 6
th
in a test.
1. Introduction
Page 4


Data 
Handling
Topics to be Covered 
1.Introduction
2.Organising Data by using tally marks
3.Pictographs
4.Interpretation of a Pictograph
5.Drawing a Pictograph
6.A bar graph 
7.Interpretation of a bar graph
8.Drawing a bar graph
DATA HANDLING
Data is a collection of numbers gathered to give some 
information.
For Example: 
?Record the attendance of students in  a class every day.
?Marks obtained by a student after every test or examination.
?Age of all students of your class.
?Choice of sweets or fruits of the students of class 6
th
.
?Size of shoes of students in class 6
th
.
?Marks obtained by all the students of class 6
th
in a test.
1. Introduction
To get particular information from the given data quickly,
the data has to organised or arrangement first. The
organisation of data can be done in one of the following
ways:.
?Ascending or descending order.
?Organising data by using tally marks.
?By using pictographs
?By using bar graphs
2. Organising of Data
Page 5


Data 
Handling
Topics to be Covered 
1.Introduction
2.Organising Data by using tally marks
3.Pictographs
4.Interpretation of a Pictograph
5.Drawing a Pictograph
6.A bar graph 
7.Interpretation of a bar graph
8.Drawing a bar graph
DATA HANDLING
Data is a collection of numbers gathered to give some 
information.
For Example: 
?Record the attendance of students in  a class every day.
?Marks obtained by a student after every test or examination.
?Age of all students of your class.
?Choice of sweets or fruits of the students of class 6
th
.
?Size of shoes of students in class 6
th
.
?Marks obtained by all the students of class 6
th
in a test.
1. Introduction
To get particular information from the given data quickly,
the data has to organised or arrangement first. The
organisation of data can be done in one of the following
ways:.
?Ascending or descending order.
?Organising data by using tally marks.
?By using pictographs
?By using bar graphs
2. Organising of Data
Tally marks are a way of expressing number in groups of 
five. The numbers are represented as follows :
Organising Data by using 
Tally marks
1
2
3
4
5
6
7
8
9
10
I
II
III
IIII
IIII
IIII I
IIII II
IIII III
IIII IIII
IIII IIII
One vertical line
Two vertical line
Three vertical line
Four vertical line
Diagonal across four vert. line
Five +1 vertical line
Five +2 vertical line
Five +3 vertical line
Five + 4 vertical line
Five + Five 
Note:- IIII  or IIII   = 5 , Both symbols are correct
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FAQs on PPT: Data Handling

1. What are the different types of data representation used in Class 7 Mathematics Olympiad?
Ans. Data representation includes bar graphs, pictographs, line graphs, pie charts, and histograms. Bar graphs display categorical data using rectangular bars of equal width. Pictographs use symbols to represent data values. Line graphs show trends over time by connecting points. Pie charts represent parts of a whole using circular sections. Histograms display frequency distribution of continuous data. Each method serves different purposes depending on the data type and comparison needs.
2. How do I calculate the mean, median, and mode for a dataset in data handling questions?
Ans. Mean is the average-sum all values and divide by the total count. Median is the middle value when data is arranged in order; for even counts, average the two middle numbers. Mode is the value appearing most frequently. These measures of central tendency help summarise large datasets. For grouped data, use class midpoints to calculate mean. Understanding which measure to use depends on data distribution and outliers present in the problem.
3. Why is the range important when comparing data sets in CBSE Class 7?
Ans. Range measures data spread by subtracting the minimum value from the maximum value, showing variability. A large range indicates scattered data; a small range suggests clustered data. Range helps identify outliers and understand consistency. However, range alone doesn't fully describe distribution since it only considers extreme values. Combined with mean and median, range provides comprehensive data analysis. This concept is essential for comparing datasets effectively in Olympiad problems.
4. What's the difference between frequency and cumulative frequency in data handling?
Ans. Frequency counts how many times a value appears in a dataset. Cumulative frequency is the running total-it adds each frequency to the sum of all previous frequencies. Cumulative frequency helps identify quartiles and percentiles in grouped data. It's particularly useful for constructing ogive curves and finding median class intervals. Understanding this distinction is crucial for interpreting frequency distribution tables accurately during Olympiad examinations and data analysis tasks.
5. How do I read and interpret a histogram correctly for Class 7 Maths questions?
Ans. A histogram displays continuous data using adjacent rectangular bars where the area represents frequency. The x-axis shows class intervals; the y-axis shows frequency density or frequency. Read values by identifying bar heights and class widths. Unlike bar graphs, histogram bars touch each other without gaps. Frequency equals height multiplied by class width for grouped data. Histograms reveal distribution shape, central tendency, and variability-essential skills for data handling problems in Mathematics Olympiad preparation.
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