Data handling means collecting the set of data and presenting it it in a different form. Data is a collection of numerical figures that represents a particular kind of information. The collection of observations which are gathered initially is called raw data. Data can be in any form. data collection to data representation. investment banking, maths presentation personal education school college university

1. 0
1
2
3
4
5
BY SUDHANSHU MEHANI

2. In your day-to-day life, you might have come across information, such as:
• Runs made by a batsman in the last 10 test matches.
• Number of wickets taken by a bowler in the last 10 ODIs.
• Marks scored by the students of your class in the Mathematics unit test.
The information collected in all such cases is called data. Data is usually collected in
the context of a situation that we want to study
BY SUDHANSHU MEHANI

3. Usually, data available to us is in an unorganized form called raw data. To draw
meaningful inferences, we need to organize the data systematically so that we
can represent it in a such way that one can understand
Collect Data Organize Data
Data
representation
First Step is Collecting
Data for example a
teacher can ask students
to tell their favorite
subjects one by one
Second Step is
Organizing Data
the teacher will write
down the choices of
students one by one and
convert it into a tally
system
Third step is Data
Representation
Once the teacher has collected
the data and organized it she
or he can chose their favorable
method of data representation
Three steps to Represent data
BY SUDHANSHU MEHANI

4. Subject Tally Marks Number of Students
Art | | | | | | 7
Mathematics | | | | 5
Science | | | | | 6
English | | | | 4
The number of tallies before each subject gives the number of students who like thatparticular subject.
This is known as the frequency of that subject.
Frequency gives the number of times that a particular entry occurs.
From Table, Frequency of students who like English is 4 Frequency of students who like Mathematics is 5
The table made is known as frequency distribution table as it gives the numberof times an entry occurs.
BY SUDHANSHU MEHANI

5. Sometimes, data is represented graphically to give a clear idea of what it represents.
Few examples of Data representation are below:-
Pictograph
Bar graph
Double Bar Graph
Pictorial representation of data
using symbols.
= 100 cars  One symbol stands for 100 cars
July = 250
1
denotes 2 of 100
August = 300
September = ?
Adisplay of information using bars of uniform
width, their heightsbeing proportional to the
respective values.
Abar graph showing two sets of data
simultaneously. It isuseful for the
comparison of the data.
BY SUDHANSHU MEHANI

6. 0
10
20
30
40
50
60
School A School B School C
Walking Cycling
0
10
20
30
40
50
60
School A School B School C
Walking
0
5
10
15
20
25
30
35
40
45
50
School A School B School C
Cycling
Children who prefer School A School B School C
Walking 40 55 15
Cycling 45 25 35
A table below shows data of three schools School A School B and School C and number of
students in each schools preferred mode of travelling to school
Bar Graph 1 Bar Graph 2
Double Bar Graph
Graph 1 Graph 2 are individual graph showing no of students using cycling and walking and
third graph is a double bar graph compering data of both the graphs
BY SUDHANSHU MEHANI

7. The information in slide 4 where we understand about frequency distribution
where the size of the data was small but sometimes we need to deal with large
number of data. We can group the data inro intervals to represent the data in an
understandable manner.
Example
consider the following marks (out of 50)
obtained in Mathematics by 60 students of
Class VIII:
21, 10, 30, 22, 33, 5, 37, 12, 25, 42, 15, 39, 26,
32, 18, 27, 28, 19, 29, 35, 31, 24,36, 18, 20, 38,
22, 44, 16, 24, 10, 27, 39, 28, 49, 29, 32, 23,
31, 21, 34, 22, 23, 36, 24,
36, 33, 47, 48, 50, 39, 20, 7, 16, 36, 45, 47, 30,
22, 17.
Groups Tally Marks Frequency
0-10 | | 2
10-20 | | | | | | | | 10
20-30 | | | | | | | | | | | | | | | | | 21
30-40 | | | | | | | | | | | | | | | | 19
40-50 | | | | | | 7
50-60 | 1
Total 60
Class Intervals
0 - 10
Lower class limit Upper class limit
BY SUDHANSHU MEHANI

8. No.
of
students
Marks obtained By students
Class Intervals Frequency
0-10 2
10-20 10
20-30 21
30-40 19
40-50 7
50-60 1
BY SUDHANSHU MEHANI

9. Circle Graph shows the relationship
between a whole and its parts. Here, the whole circle is
divided into sectors. The size of each sector is
proportional to the activity or information it represents.
Flavors Percentage of students
Preferring the flavors
Chocolate 50%
Vanilla 25%
Other flavours 25%
The total angle at the center of a circle is 360°. The central angle of
the sectors will be a fraction of 360°. We make a table to find the central
angle of the sectors
Flavours Students in per cent
preferring the flavours
In fractions Fraction of 360°
Chocolate 50% 50 = 1
100 2
1
2 of 360° = 180°
Vanilla 25% 25 = 1
100 4 1
4 of 360° = 90°
Other
flavours
25%
25 = 1
100 4
1
4 of 360° = 90°
50
25
25
Chocolet Vanillia Other Flavours
BY SUDHANSHU MEHANI

10. . Radius
.
New Radius
Step 1 – Draw a Circle with a Compass
Step 2 – Draw The Radius
Step 3 – Get a Protractor and align it with the radius
Step 4 – Mark the calculated angle using a pencil
Step 5 – Draw a line and from the center point
Step 6- as soon as you draw the line, that line will new radius
Step 7 – Keep the protector on the new radius and repeat step 4 and 5
Step 8 – Shade and label different parts
BY SUDHANSHU MEHANI

11. You face a lot of situations such as
those where you take a chance and it
does not go the way you want it
• Train being on time
• Getting a lottery
• Tossing a coin ( Heads or Tails )
Number of tosses Tally marks (H) Number of heads Tally mark (T) Number of tails
50 | | | | | | | | | | | |
| | | | | | | | | |
27 | | | | | | | | | | | |
| | | | | | |
23
60 | | | | | | | | | | | |
| | | | | | | | | | |
28 | | | | | | | |.
|| | |
| | | | | | | | | | | | | |
32
70 ... 33 ... 37
80 ... 38 ... 42
90 ... 44 ... 46
100 ... 48 ... 52
BY SUDHANSHU MEHANI

12. • Probability means possibility
• It deals with the occurrence of a random even
• The value is expressed from zero to one.
• The meaning of probability is basically the
extent to which something is likely to happen.
• To find the probability of a single event to
occur, first, we should know the total number
of possible outcomes.
Probability of event to happen P(E) = Number of favourable outcomes
Total Number of outcomes
There is a container full of coloured bottles, red, blue,
green and orange. Some of the bottles are picked out and
displaced. Sumit did this 1000 times and got the following
results:
•No. of blue bottles picked out: 300
•No. of red bottles: 200
•No. of green bottles: 450
•No. of orange bottles: 50
What is the probability that Sumit will pick a green bottle?
Ans: For every 1000 bottles picked out, 450 are green.
Therefore, P(green) = 450/1000 = 0.45
BY SUDHANSHU MEHANI