Figure 1: Parameters and weight-ages in Outlook-Cfore Survey 2006 India’s Top B-schools
Therefore, the students have a wide range of options to choose from which the institution to pursue their interests or on which b-school they find maximum placement section-wise. As the students bear the complete expenditure of education, they deserve the best education. Therefore, section-wise placement offer has become a competitive weapon for the top b-schools to serve and attract their primary students.
Objective of the Study
The main objective of the study is to determine the effect on performance of India’s top B-Schools on the basis of average salary package offered to students in different sectors. And also what is the effect on performance of average salary package in different sectors offered by India’s top B-schools.
Research Methodology
We have collected secondary data of average salary package of IIMs in 2011 in different sectors. We applied ANOVA analysis (two way analysis of variance) to determine the effect of salary package in different sectors offered to students of India’s top b-schools and vice-versa. The average sector-wise placement in 2011 (In LPA) for the three top b-schools (IIM-A, IIM-I, IIIM-K) are shown in table 1.
Table 1: Secondary Data (Average placement in different functions of Top B-School in 2011, In LPA)
Source: IIMs Websites
ANOVA Analysis
Two-way Analysis of Variance
1. Formulation of Hypothesis:
Null Hypothesis for treatments, H0: µ1 = µ2 = µ3 = µ4
i.e., average salary package (mean) in all four IIMs are equal
Alternate Hypothesis for treatments, H1: µ1 ≠ µ2 ≠ µ3 ≠ µ4
i.e., average salary package (mean) in all four IIMs are not equal
Null Hypothesis for Blocks, H0: µ1 = µ2 = µ3 = µ4
i.e., average salary package (mean) in all Sectors or functions are equal
Alternate Hypothesis for Blocks, H1: µ1 ≠ µ2 ≠ µ3 ≠ µ4
i.e., average salary package (mean) in all sectors or functions are not equal
2. Level of Significance:
Let it be α = 5%
3. Test Statistics
Calculation of Grand Total:
G =
Calculation of Correction Factor:
C.F. =
, here n=b*k, b= number of blocks (Columns), k = number of treatments (Rows)
Calculation of Raw Sum of Squares:
RSS =
2
Calculation of Total Sum of Squares:
TSS = Raw sum of squares (RSS) - Correction factor (C.F.)
Calculation of Treatment Sum of Squares:
TrSS = ∑
Calculation of Block Sum of Squares:
BSS = ∑
.
Calculation of Error Sum of Squares:
ESS = TSS - TrSS - BSS
Table 2: ANOVA Table for analysis of variance
4. Formulation of Tabulated Value:
Tabulated Value = Expected value found from F Table at specific level of significance.
Fe1 [αe, {k-1, (k-1)x(b-1)}df]
Fe1 [αe, {b-1, (k-1)x(b-1)}df]
5. Interference:
If F > Fe1, reject null hypothesis.
If F < Fe1, do not reject null hypothesis.
If F > Fe2, reject null hypothesis.
If F < Fe2, do not reject null hypothesis.
Analysis & Findings with Implications
Firstly we found out some statistics function such as mean, median, variance; standard deviation, coefficient of correlation etc. on given secondary data are shown in table 3 & 4 with formulae.
Table 3: Some Statistics Functions (Mean, Median & Variance etc.)
Table 4: Statistics Functions (Coff. of variation etc.)
We selected four major functions or sectors of average placement data for ANOVA analysis of 4 different top b-schools (IIM-A, IIM-I, IIM-K, IIM-B) as shown in table 5.
Table 5: Placement data of four Top B-Schools for ANOVA Analysis
Now, apply two way analysis of variance or ANOVA Analysis
Null Hypothesis for treatments, H0: µ1 = µ2 = µ3 = µ4
i.e., average salary package (mean) in all four IIMs are equal
Alternate Hypothesis for treatments, H1: µ1 ≠ µ2 ≠ µ3 ≠ µ4
i.e., average salary package (mean) in all four IIMs are not equal
Null Hypothesis for Blocks, H0: µ1 = µ2 = µ3 = µ4
i.e., average salary package (mean) in all Sectors or functions are equal
Alternate Hypothesis for Blocks, H1: µ1 ≠ µ2 ≠ µ3 ≠ µ4
i.e., average salary package (mean) in all sectors or functions are not equal
Level of Significance: Let it be α = 5%
Test Statistics
Grand Total: G =
= 217.06
Correction Factor: C.F. =
= 2944.69, here n=b*k
b= number of blocks (Columns) =4, k = number of treatments (Rows) =4
Raw Sum of Squares: RSS =
2 = 2974.16
Total Sum of Squares: TSS = RSS - C.F. = 2974.16 – 2944.69 = 29.47
Treatment Sum of Squares: TrSS = ∑
= 8.4875
Block Sum of Squares: BSS = ∑
. = 7.9725
Error Sum of Squares: ESS = TSS - TrSS – BSS = 13.01
Table 6: ANOVA Analysis for variance
Formulation of Tabulated Value: Tabulated Value = Expected value found from F Table at specific level of significance.
Fe1 [αe, {k-1, (k-1)x(b-1)}df] = Fe1 (0.05, (3, 9)df) = 3.86
Fe1 [αe, {b-1, (k-1)x(b-1)}df] = Fe2 (0.05, (3, 9)df) = 3.86
Inference: F1 < Fe1, 1.958 < 3.86
Do not reject null hypothesis i.e. average salary package in all four IIMs are equal.
&
F2 < Fe2, 1.839 < 3.86
Do not reject null hypothesis i.e. average salary package (mean) in all sectors or functions are equal.
Conclusion & Scope of the Study
It has been found from above ANOVA analysis the average package offered by Top India’s B-School IIM-A, IIM-I, IIM-K & IIM-B in Marketing, IT, Finance and operations sectors are equal. There is no impact on the performance of India’s Top B-Schools’ average salary package for students in different sectors and vice-versa.
So the students don’t have any preference for particular sector for India’s Top B-Schools. As all the sectors offer same average package. Hence they accept any sector offered to them.
Bibliography
Thomas, H. and Thomas, L. (2011), “Perspectives on leadership in business schools”, Journal of Management Development, Vol. 30 No. 5
Ranjan, J. (2011), “Study of sharing knowledge resources in business schools”, The Learning Organization Vol. 18 No. 2, pp. 102-114
Outlook Magazine (2006), September 16.
Elder, B. and Sneed, J. (2011), “Legal implications of helping students find employment”, Management Research Review, Vol. 34 No. 6, pp. 702-711
http://www.iimahd.ernet.in/iprs/gallery/PGP_Placement_%20report_11.pdf
http://www.iimk.ac.in/placement/finalplacement2011.php
http://www.iimidr.ac.in/iimi/media/pdf/2011%20PlacementReport.pdf
http://www.iimb.ernet.in/docs/pgp/Glimpses2011.pdf