1. STATISTICS PROJECT Priya Mariam Simon Aparna Rajeev Sudhit Sethi
Jinto Antony Kurian

2. Objective
The main objective of our project is to acquire in-depth understanding of collection, organization and interpretation of numerical facts for taking managerial decisions. The data for the project has been collected from the Outlook (India) site. We have referred the link for the top 100 engineering colleges in India.

3. Variables
Here the variables used are Nominal variables, Ordinal variables and some other variables. Nominal variables used are Name of the Institution, City and G/P (Government/Private). The ordinal variable used is Rank. We have also used various other variables such as IC (Intellectual Capital), I&F (Infrastructure and Facilities), PS (Pedagogic Systems), II (Industry Interface) and P (Placement).

4. Attributes
IC (Intellectual Capital) represents quality of students each institute possesses.
I&F (Infrastructure and Facilities) include land, building and various other facilities which an institute possesses.
PS (Pedagogic Systems) refer to instructional methods used for educational purposes.
II (Industry Interface) means corporate interaction with the college.
P (Placements) refer to campus recruitments

5. Frequency Distribution Table
Class interval
midpoints(x)
frequency(f) cf fx d
d^2
fd^2
50-55
52.5
-18.05
55-60
57.5 5
287.5
-13.05
60-65
62.5 21 26
1312.5
-8.05
65-70
67.5 33 59
2227.5
-3.05
9.3025
70-75
72.5 18 77
1305
1.95
3.8025
68.445
75-80
77.5 10 87
775
6.95
80-85
82.5 92
412.5
11.95
85-90
87.5 2 94
175
16.95
90-95
92.5 99
462.5
21.95
95-100
97.5 1
100
26.95
7055

6. Statistical details
Mean
Median
Mode
S.D
70.55
66.65
65.1
8.66

7. The Histogram above shows each separate class in the distribution
The Histogram above shows each separate class in the distribution. In the above histogram, we have 5 elements in the class between 55 to 60.

8. Frequency Polygon
Frequency Polygon shows the outline of the data pattern more clearly.

9. Less than ogive
The Ogive curve above is a graphical representation of the cumulative frequency distribution.

10. Pie Chart showing distribution of Engineering Institutes

11. Table showing Correlation and Regression between IC & P
0.81
slope
0.57
intercept
0.71
R^2 R

12. Correlation & Regression line

13. Table showing Correlation and Regression between II & P
Correlation coefficient
Slope
Intercept
r^2 r

15. Rank correlation
1-6∑D^2+(m^3-m/12)/n(n^2-1)
sum of squares of the differences D
14768
no. of repetitions m
2382
Rank correlation
The rank correlation is calculated by the method of sum of the squares of the differences of the rank. Since we have repetitive ranks, a modified formulae is used which is shown in the above tabular column.
Using this approach the Rank Correlation is found to be .9101

16. Probability Frequency Government Private Total 50-60 5 13 18 60-70 2823 51
70-80 17 3 20
80-90 7 1 8
90-100 60 40
100

17. Cont…
What is the probability that a college selected at random falls in the range 70-80?
P(E)= 20/
What is the probability that a college selected at random is a private college and falls under the range ? P(E/P) = 23/
What is the probability that a college selected at random is a government college
or falls under the range 80 to 90?
P(gUE) = P(g) + P(E) - P(g∩E) = 60/ / /100
0.08

18. Normal Distribution A continuous distribution.
Shows the distribution of data as an area under the curve.
From the data, 72% of colleges lie between 65 and 90.
Right skewed curve.