2. Definition of statistics
• Statistics concern with techniques by which collecting
information,organizing,analyzing and interpreting data.The
ultimate aim of this process is to forecast and making
decisions regarding any field.
3. Quantitative data
•Qualitative data
Quantitative data is numbers-based, countable, or
measurable. Qualitative data is interpretation-based, descriptive,
and relating to language. Quantitative data tells us how many, how
much, or how often in calculations. Qualitative data can help us to
understand why, how, or what happened behind certain behaviors.
•
Qualitative data is the descriptive and conceptual findings
collected through questionnaires, interviews, or
observation. Analyzing qualitative data allows us to explore
ideas and further explain quantitative results.
4. 1. Identify whether the following variable type are quantitative or
qualitative ?
a) Number of family members
b) Color of pens
c) Gender
d) Age of Olympians
e) Weight
f) Hight
g) Happiness rating
Quantitative data Qualitative data
• Number of family members * Color of pens
• Age of Olympians * Happiness rating
• Weight
• Hight
5. • Level of measurement
There are 4 type of measurement
1. Nominal scale
2. Ordinary scale
3. Interval scale
4. Ratio scale
Method of data collection
Primary data Secondary data
Direct personal investigator Internation publication (IMFWB)
Indirect oral interview CBSLWeb site
Self administrated (E-mail) survey Dept. Census and
Information through agencies Financial firms publication
Focus group Reports,journals,Magazines
6. Diagrammatic representation
• Diagrams can be identified as representing data in the visual platform when
using statistical dataThe reasons for using diagrams are to have a clear
understanding about the data , to analyze and compare the data to forecast
future values regarding any specific situation.
Bar diagram
Bar chart are used to represent categorical and discrete data there are
four type of bar chart
• Simple bar chart
• Component bar chart
• Percentage component bar chart
• Multiple bar chart
7. 1. Simple bar chart
• following data are given for a school total marks for students for six years.
P present the bar chart
Year Marks
2001 200
2002 450
2003 275
2004 350
2005 435
2006 525
200
450
275
350
435
525
0
100
200
300
400
500
600
2001 2002 2003 2004 2005 2006
marks
8. Component bar chart
0
20
40
60
80
100
120
140
saman Kamal Sunil Amal
Car Bus Bicycle
The below table is regarding the favorite vehicles of Saman,Kamal,Sunil,Amal
from car,bus,bicycle .represent these data in a component bar chart.
Person Car Bus Bicycle
Saman 20 35 35
Kamal 30 45 50
Sunil 40 25 26
Amal 50 23 34
9. Percentage component bar chart
following information about how much money was spent on computers and smartphones in
country X
year computer smartphone
2011 30 10
2012 35 10
2013 40 10
2014 45 30
2015 50 45
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
2011 2012 2013 2014 2015
comuter smartphones
10. Multiple bar chart
year computer smartpho
ne
2011 30 10
2012 35 10
2013 40 10
2014 45 30
2015 50 45
Following information about how much money was spent on computers and smartphones in
country X
0
5
10
15
20
25
30
35
40
45
50
2011 2012 2013 2014 2015
computer smarphones
11. Pie chart
• A pie chart is a graphical representation technique that displays data in a circular-
shaped graph. It is a composite static chart that works best with few variables. Pie
charts are often used to represent sample data—with data points belonging to a
combination of different categories.
Year Profit
1999 1500
2000 850
2001 650
1500 *360 = 180
3000
850 *360 = 102
3000
650 * 360 = 78
3000
Sales
1999 2000 2001
12. Line chart
A line chart is a graph which displays information as a series of data on a line
the different between scatter plot and line chart is, it is required to draw or
connect the points of the graph in a line chart but not in a scatter plot
time speed
0 0
1 3
2 7
3 12
4 20
5 30
0
5
10
15
20
25
30
35
0 1 2 3 4 5
speed
13. Correlation analysis
Types of correlation
1. Positive correlation -price and quantity supply
2. Negative linear correlation - price and quantity demand
3. No linear correlation - price of garments and quantity of raw rice available
14. Price (x) Qd (Y) xy x2
𝒚𝟐
10 10 100 100 100
20 08 160 400 64
30 05 150 900 25
40 03 120 1600 9
50 02 100 2500 4
60 01 60 3600 1
x =210 y =29 xy =690 𝐱𝟐 =9100 𝐲𝟐 =203
• The following information ia about price and it quantity demand
1. Calculate coefficient of correlation ?
2. Calculate the rank coefficient of correlation?
15. Linear Regression analysis
Price (x) Qd (Y) xy 𝑥2
10 10 100 100
20 08 160 400
30 05 150 900
40 03 120 1600
50 02 100 2500
60 01 60 3600
x =210 y =29 xy =690 𝑥2
=9100
1. Calculate the regression line for following information
16. Regression line
Y = 11.34 -0.186x , x=20 ,x =50
Y= 11.34 -0.186* 20 y = 11.34 – 0.186* 50
y = 11.34 – 3.72 y = 11.34 – 9.3
Y =7.62 y =2.04
9.48
7.62
5.76
3.9
2.04
0
1
2
3
4
5
6
7
8
9
10
10 20 30 40 50
17. Statistical measures
Statistical measures or central tendency is important to represent set of
data the major measurement of statistical measures are mean ,median and
mode.
Mean
Mean is a series of a data obtain from relevant observation and taking to
the sum of observation ,dividing by no of observations. Initially mean can
be calculated as follows .
simple arithmetic
weighted arithmetic
Mean = fx
n
18. Direct method
Mean = fx
n
= 15 + 20 + 30 +22 + 25 +18 +40 +50 +55 +65
10
= 34
• Pocket allowance of students is 15,20,30,22,25,18,40,50,55,65
Find out the average pocket allowance.
19. frequency ( Discrete series )
Following data are given for the marks obtained by the student in the
mathematics paper.
Marks (X) Number of
student (f)
Fx
10 2 20
20 3 60
30 7 210
40 6 240
50 5 250
60 10 60
70 7 490
80 5 400
= 45 Fx =1730
Mean = fx
f
= 1730
45
= 38.4