Impact of Pre School Education Program of Icds on Children in Rural Punjab
Final Paper - India
1. 0
GSA 2013
Rural Children’s Aspirations
An analysis of factors contributing to the life outlooks of rural youth
Deepak Sathyanarayan
2/26/2013
Abstract
Burdens of poverty begin long before an individual has an occupation or livelihood.
Children living in impoverished areas are not only affected in regards to their lack of material
wealth, but also in a more abstract manifestation of poverty – decreased aspirations. This study
delves into the concept of rural childhood aspirations and attempts to understand the factors
that influence aspiration development. Analysis of these factors begins with the implementation
of the “Predicted Maximum Future Income” (PMFI) estimator of aspiration, which quantifies
aspiration in such a way that exposes the dynamic trajectories of occupational desires and the
interplay that occurs between aspiration and a child’s socioeconomic environment.
2. 1
Introduction
Ongoing studies in the fields of poverty
and development are being strongly focused on
the material aspects of one’s livelihood. Topics
ranging from health and disease to
demographics and resource allocation are
commonly seen in research being done across
the globe. This research has provided
sociologists and political scientists key
information for producing the international
policies and regulations that are currently in
place. However, as the research continues, new
fields of interest are emerging – branches of
the science are being pulled deeper and deeper
into the micro – into the desires of individuals.
One may wonder, “What is the point of
looking into an individual’s desires if the
socioeconomic and political poverty still
persists? It is the physical world, after all,
which is directly affecting those in poverty.”
True, the lack (or denial) of basic material and
social wealth is the foundation of poverty seen
worldwide. But, what is to be said if those
impoverished are not having the fundamental
desire to improve their standard of living?
Individuals that are not setting their sights to a
life outside of poverty cannot be expected to
suddenly be found in a well-to-do condition in
the future. Therefore, it can be said that by
simply aspiring to be something, individuals
are one step closer to moving out of poverty.
Studies dealing with the present condition of
various aspects of one’s life only provide a
snapshot of poverty’s status. By taking into
consideration the aspirations and desires of
those in the developing world, research
findings would provide insight into the future
persistence and propagation of impoverished
livelihoods. Equipped with such information,
policy makers will be able to structure
regulations to not only suit those in need today,
but also those in need years down the road.
In order to plan for the future
socioeconomic demographic, one must not
simply look at the desires of everyone in
poverty, but should look specifically at the
desires of the youth. Child aspirations, in
comparison to those of a working adult, are
very powerful driving forces that strongly
shape the future outlooks of that individual.
This can be said simply due to the sheer
plasticity of path choices one has available in
childhood versus adulthood. Since childhood
motivations can be a powerful indicator of
future success, it is important to fully
understand the various components of youth
aspiration and the factors that can affect it. For
this reason, obtaining a deeper understanding
of the factors contributing to the development
of childhood aspirations is the key to clearly
viewing the present and future micro-dynamics
of poverty.
The following research study takes into
account four broad topics of interest: the child,
parents input, government involvement, and
NGO efforts. Each of these categories are
broken down further through the course of the
3. 2
research – each section delving into various
proposed factors that are thought to have some
influence on the aspiration building of rural
children. With regards to the child, some
proposed factors include gender, school
conditions, development status of residence,
and parents’ occupation. Regarding parents,
the duration and extent of interest parents took
in their child’s future were primarily observed.
Government and NGO efforts were taken into
consideration as well, with concern given to the
pros and cons of any currently active policy. By
looking into each of these proposed
contributing factors, the extent to which each
factor affects the development of aspirations
will be determined.
Ideal Conceptual Scenario
Since many of the children in this
research are school-going, this section serves to
provide an overview of how the education
system is structured in the observed areas
[Table 1]. In addition, the idealized system
functionality, responsibility allocations, and
resource distribution dictated by government
and NGO policy will be discussed with regards
to the villages of Ramad, Sava, Sava Kheda and
Murgi Kheda1 in Rajasthan, India.
Ramad: In this village, there are two
schools available – one private primary school
(1st -5th grade) and one government secondary
1 Village names have been changed to preserve the
confidentiality of those mentioned in this study.
Location School Facilities
Ramad
Private Primary School
Secondary Government School
Sava
Primary Government School
Secondary Government School
Murgi Kheda
1 Anganwadi
Primary Government School
Sava Kheda Primary Government School
Table 1: School facilities at each of the
research areas observed.
school (1st -9th grade). Ramad’s private primary
school has 147 students and 3 teachers
available. The secondary government school
has 179 students and 4 teachers available. One
of the more developed villages in the area,
Ramad has a diverse occupation distribution of
its residents as well as an adequate supply of
water and other resources. With its wealth,
Ramad serves as a hub for many of the
surrounding undeveloped areas.
Sava: This village is approximately 3 km
from Ramad and is much more developed, with
a central market and large, well maintained
secondary government school (6th-12th grade).
There are 7 teachers on staff to teach the
approximately 286 students attending. The
Primary government school in Sava is much
smaller than the secondary school, with only 19
students (1st-5th grade) and only 1 teacher on
staff.
Murgi Kheda: Approximately 2 km from
Ramad by foot, this village is relatively
undeveloped and is home to the scheduled
tribe (ST) peoples. All of the adults in the area
are farmers in the monsoon season and
laborers in the summers. The government
4. 3
primary school in Murgi Kheda has 65 students
and 3 teachers on staff. In the area, there is an
anganwadi as well, which serves as a 1st and 2nd
grade school for those who may live too far
away from the primary government school.
Sava Kheda: As Murgi Kheda is for
Ramad, Sava Kheda is to Sava. This village is
around 2km from Sava, and since it is closer to
a more developed “hub village”, many of the
adults in this area take up labor occupations
instead of farming. In Sava Kheda, there is one
primary government school (1st-5th grade) with
46 students and 1 teacher on staff.
Across all of these schools and areas,
national government policies are currently in
place. In total, there are four observed
government schemes active: Swachchh
(“Cleaning”) Project, Right to Education (RTE),
Mid-Day Meal (MDM), and Right to
Information (RTI). Swachchh is a large nation-
wide effort to push more social and political
power to the periphery of the Indian
governance structure (i.e. local governments).
In doing so, more power (and funds – max 5
crore rupee per year) is given straight to the
local village government, called the Panchayat.
These funds are to be used by the Panchayat to
spur development and economic growth within
their respective villages. Swachchh also targets
school development by putting in place a
“School Management Committee (SMC)” that
is to overlook and supervise activities in the
government schools. The SMC is established
for each government school and is comprised
of the headmaster, one teacher, 11 parents, and
one student. Alongside this, the RTE scheme
guarantees students attending school 45 days
out of the year passage into the next grade
(until 8th grade). At these schools, the MDM
scheme is in place to ensure a mid-day meal to
every government school student each day. The
distribution of the food stuffs is the
responsibility of the state government, who has
the option of contracting out distribution
services to NGOs and other organizations. As
an effort to increase the transparency of
government policy and activities, the RTI
scheme gives any individual the power to ask
the local and state government for any publicly
disclosed information.
Supplementing government efforts to
spur education, NGOs in the area, such as
Gandhi Manav Kalyan Society (GMKS), have
been trying to pull children from farming,
livestock, and labor – pushing them to attend
school. The efforts of GMKS focus
predominantly on the children in rural areas
who are of primary school age (6 – 14 years).
Methodology
The adopted methodology has been
formed as to test for the various factors that
affect the development of child aspirations as
well as analyze the efficiency and effectiveness
of government and NGO programs in the
villages of Ramad, Sava, Murgi Kheda, and
Sava Kheda.
5. 4
Target Audience Leading Questions
3rd, 5th, 8th, and 9th
grade students in
the each education
facility noted in
“Table 1”
Why do you come to school?
Do your parents urge you to come to school?
If they stopped, when did you start coming on your own?
What are your parents’ jobs?
Do you want to continue doing that job in the future?
If not, what do you want to become?
Parents of students
in each of the
education facilities
What grade is your child in?
Does your child go to school on his/her own?
Do you have any jobs that you are urging your child to pursue?
If child is no longer in school:
When did your child stop going to school?
Why did they stop attending?
Was there any encouragement to return to school?
Government
Officials and NGOs
What efforts are being done with regards to children’s’ education?
What has resulted from these efforts?
What obstacles are arising?
Table 2: Leading questions used for gathering key information from students, parents, government
officials and NGO representatives
The core methods used is comprised of
interviews with four distinct groups: students,
parents, government officials, and NGOs.
Samples of questions asked during these
interviews can be seen above [Table 2].
Student Interviews: Each of the schools
noted in “Table 1” (excluding the anganwadi)
were approached at the beginning of the school
day or after recess for a “class discussion and
study” to be held. After gaining approval from
the headmaster or supervising teacher,
classrooms were entered with brief
introductions regarding the study and its
points of interest. To help students, especially
those in 3rd and 5th grade, feel comfortable, a
15-20 minute discussion was held regarding
topics ranging from recent events in the
villages, recreation, school lessons, weather,
poem recitation, and jokes. Also, teachers were
requested to leave the room for the duration of
the discussions to help minimize any fears or
biases the students may be having with the
teacher present in the classroom. Once the
students were relaxed, the first of the questions
in the above table was asked. Responses were
taken individually in the classroom setting.
Ideally, private interviews would be conducted
with each student, but due to time restraints,
answers were collected in a group discussion
format. Translations of interview responses
were noted down in a table for future analysis.
Parent Interviews: Shortly after school
finishes for the day, student’s parents begin
returning home via auto- rickshaw or tempo
from their respective labor sites, farms, or
stores. It was generally during this time that
parents were available to talk for 10-15 minutes
while waiting for the next auto-rickshaw. After
a short introduction regarding the nature of the
study, parents were asked the set of questions
6. 5
seen above [Table 2]. Stay-at-home parents
were also interviewed when found in their
village homes. A minimum of 3 parents were
interviewed from each type of school [Table 1].
Translations of interview responses were noted
down for future analysis.
Government and NGO Interviews: In
order to inquire about government policies and
NGO activities, representatives of each group
were interviewed separately, using the
corresponding questions found in “Table 2” as
a basis of discussion. Regarding government
efforts and policies, and following individuals
were interviewed: Sarpanch (Ramad and Murgi
Kheda), Upsarpanch, Nodal of Education, and
a local Reporter. When interviewing for NGO
activities, a fieldworker from GMKS (the only
functioning NGO in these areas) was, too,
asked the questions seen above.
To conduct an analysis of the data
collected from the students, an estimator by
which “aspirations” can be measured was to
first be developed. Thus, a measure termed the
“Predicted Maximum Future Income (PMFI)”
has been chosen to be used as an indicator of
an individual’s aspirations.
PMFI: This estimator is simply the
expected (or average) income of the occupation
an individual aspires to take on. This method of
estimation is based off of the chain of thought
which concludes, “It can be assumed that an
individual will not obtain an occupation higher
than that which he/she aspires to achieve.” In
addition to providing a quantifiable measure of
aspirations, PMFI allows the researcher to
remove other extraneous variables that may be
biasing the analysis. Due to the simplicity of
the measurement, PMFI can be easily set using
national, regional, or local income averages to
accommodate a variety of study scopes.
However, the high specificity of the estimator
limits its use across regions, where policy and
social differences may greatly affect the
incomes of various occupations.
Implementing PMFI: Following the
student interviews, the tallies of desired
occupations were summed up and fed into the
PMFI estimator. The resulting PMFI-value is
able to manipulated to fit any group of interest.
With regards to this research, the correlation
between student PMFI-value and the following
conditions will be evaluated:
Grade of Student (3rd, 5th, 8th, 9th)
Type of School (Private vs. Government)
Development Status of Residence Area
Gender (Male vs. Female)
Parents Occupation
Due to the lack of comprehensiveness of
the samples interviewed, analysis of each of the
variables will be fragmented. This is to say that,
for example, when analyzing the PMFI vs.
Grade correlation, only the secondary
government schools in Ramad and Sava will be
taken into account because these schools are
the only observed schools with all 4 grades of
interest in the same area while being taught
from the government curriculum. Since the
government’s RTE scheme is ending at the 8th
7. 6
grade, a student t-test (one-tail, unequal
variances) will be done in order to see if there
is a statistically significant change at that
transition period between 8th and 9th grade.
Likewise, when studying the private vs.
government school comparison, only select
government schools have been included since
the government schools greatly outnumber the
private institutions in the observed areas. In
addition, because the private school studied
was only a primary school, grades 3 and5 are
only be taken into account. The private vs.
government school PMFI relationship for these
two grades has been run through a student t-
test to check if any existing overall differences
are statistically significant.
With regards to correlations with
development status, only 3rd and 5th grades of
primary government schools have be taken into
account because only such schools were found
in each of the areas of interest. Areas were
categorized as “Undeveloped” (Murgi Kheda
and Sava Kheda), “Developing” (Ramad), and
“Developed” (Sava). The private school in
Ramad was added into the analysis for
comparison, noted as “Developing Private”.
Analysis of PMFI and Gender has
including all individuals interviewed in all
observed areas. To help see if there are any
differences or patterns across areas with
respect to gender, the PMFI for gender has
been broken down based on area of school. The
overall gender PMFI is subjected to a student t-
test for statistical significance.
Unfortunately, one-on-one interviews
with students were not able to be conducted. As
a result, parents’ occupations on a student-by-
student basis were unable to be found.
Therefore, in order to analyze the relationship
between parent’s occupation and students’
PMFI, an average PMFI of each grade in each
area has been taken along with an average
expected income of the respective parents.
These averages are correlated against each
other in a standard regression analysis.
When looking at the data, a number of
outliers were found in which the desired
occupation was very difficult to obtain – due to
either very high skillset requirement or
severely limited openings. In addition, these
occupations had salaries approximately 10x the
average salary of the other reported
occupations. The analysis was conducted with
and without these outliers to see what impact
their presence had on the outcomes.
Supplementing the numerical analyses,
a series of anecdotal evidence has been
provided that helps view government and NGO
efforts being executed as well as thoughts and
beliefs of the various individuals interviewed
over the course of this research.
Given this description of the analysis
conducted, the following section will put forth
the information derived though the methods
discussed above.
8. 7
Results
PMFI versus Grade of Student
Through the interviews conducted
across grades 3, 5, 8, and 9, students average
PMFI have been computed and plotted, as
shown above [“Figure 1”]. In addition a student
t-test was run between 8th and 9th grade (one-
tail, unequal variances, 95% confidence
interval). For the unmodified PMFI-values, the
analysis resulted in a p-value of 0.021034,
indicating a statistically significant difference
in the 8th and 9th grade PMFI-values. For the
modified PMFI-values, the analysis resulted in
a p-value 0.143256, indicating a statistically
insignificant difference in the aspiration levels
at a 95% confidence interval.
In addition to the statistical analysis of
the data, a set of anecdotal information has
been collected through the interviews
conducted. The following paragraphs provide
the key points to be taken away from a few of
these discussions.
One of the first interviews conducted
was with the Upsarpanch of Ramad. Within the
local governance structure, this individual is
one of the top most figure heads and provided
insight about the RTE scheme. As stated
earlier, the RTE scheme allows students
passage through grades 1 to 8, given they
attend 45 days of school. “The problem is that
teachers do not need to test the children. Even
if they do, the students’ performance does not
affect whether or not they proceed to the next
class.” It was also pointed out that the issues
with RTE have been noticed by parents and the
Upsarpanch is faced with questions like, “My
child is not learning anything in the schools,
and teachers are rarely in attendance – why
should I send my child to school?” These
questions indicate not only issues with teaching
habits and curriculum, but also with teacher
attendance and accountability.
Contrasting this, a discussion with the
headmaster of the secondary government
school in Ramad indicated an effort to provide
Figure 1: Average PMFI is shown across the 3th, 5th, 8th, and 9th grades in the government schools
of Ramad and Sava. The left graph is of the unmodified data, which includes any outliers into the
analysis. The graph on the right shows the modified PMFI analysis with outliers removed. A
dashed vertical line is used to indicate the time at which the policies of the government’s Right to
Education (RTE) scheme no longer applies to the students.
0
2
4
6
8
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade in Government School
PMFI vs. Grade (Unmodified)
RTE Ends
0
1
2
3
4
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade in Government School
PMFI vs. Grade (Modified)
RTE Ends
9. 8
extra classes to students who are struggling.
The supplementary classes were offered during
the last two months of the academic school
year. An indicator used to determine those in
need of extra classes was the students’
performance on the December (“half-early”)
exams.
Another interview of interest was with a
20-year old boy in Ramad who had attempted
and failed 9th grade twice – and has now given
up. On his first attempt, he found the course
work “very difficult” and ended up failing in
multiple subjects. The following year, he
attempted the courses again, and sought help
from the teachers. However, teachers denied
him extra support, saying he “was not
performing badly enough” to require
supplementary coursework. In the second
round of exams, he passed all of his subjects,
except for math. Now the boy has been finding
work between sales at a village alcohol store
and driving auto-rickshaws.
Private versus Government School
For the purposes of this comparison,
only 3rd and 5th grades of schools in Ramad are
being compared. Student t-tests (one-tailed,
unequal variance, 95% confidence interval)
were performed with and without existing
outliers in the data. The resulting p-values
(0.1564 and 0.2537 respectively) indicate that
there is a statistically insignificant difference
between the children’s’ aspirations observed.
To supplement this data, a plot of the
PMFI-values is shown depicting the breakdown
of estimated aspirations across the 3rd and 5th
grades in private versus government schools in
Ramad [“Figure 2”].
While observing the students in and out
of the classroom setting, it was noticed that 3rd
(and even 1st) grade students in the private
school were able to properly write their names
in English. At the same time, several 3rd grade
students in the government schools of Ramad,
Sava, Murgi Kheda and Sava Kheda were
struggling to write their names in Hindi, let
alone English.
0
1
1
2
2
3
3
4
Private School Government School
PMFI(LakhRs.)
School Type
PMFI vs. School Type (Modified)
3rd
5th Modified
Overall Modified
0
20
40
60
80
100
120
Private School Government School
PMFI(LakhRs.)
School Type
PMFI vs. School Type (Unmodified)
3rd
5th Unmodified
Overall
Figure 2: Across 3rd and 5th grades in private and
government schools in Ramad, the average
PMFI-values were found. After removing an
outlier that existed in the government school’s
5th class, the data was re-plotted (below graph).
10. 9
Also in the private schools, parent-
teacher involvement and discourse is seen
more prominently as compared to the
government schools’ parent-teacher dynamic.
While being interviewed, several private school
students also indicated that they were the sons
or daughters of the government school teachers
in either Ramad or Murgi Kheda.
PMFI versus Area Development
As stated in the methodology, the
observed areas were categorized into 4 distinct
stages of development. 3rd and 5th grade
student responses were combined between
schools of the same development status,
yielding an array of PMFI-values for each
development status. Average PMFIs (with and
without outliers) were calculated and plotted
[“Figure 3”].
Upon plotting the modified data set, a
clear discrepancy in the PMFI of children in
undeveloped areas is seen. In order to test the
significance of this observation, a student t-test
was conducted between the PMFIs of
undeveloped areas and the combined array of
developing and developed PMFIs (one-tail,
unequal variances, 95% confidence interval).
The “Developing Private” category was not
included in this test since the children do not
attend the government school. The unmodified
data sets resulted in a p-value of 0.3156,
indicating no statistically significant difference
between the development levels. However, the
modified data sets resulted in a p-value of
0.00262, indicating a strong statistically
significant difference between the undeveloped
and developing/developed areas.
Through children and parent interviews,
it came through that a combination of the
following aspects differs across development
levels:
Class size (daily attendance)
Funds available & provided
Parents’ involvement in the school
Peer pressure
Teacher-student interactions
Mid-Day Meal service
A brief description of each of these
topics will be introduced now – a more in-
depth analysis will be seen in the discussion
section.
Class size: Numbers of students were
seen to vary significantly from class to class,
but the trend that appeared indicated that class
size increases with increasing development.
Figure 3: Average PMFI is displayed across
various development levels, both with and
without outliers (unmodified and modified
respectively).
0
1
2
3
4
5
6
7
8
Unmodified Modified
PMFI(LakhRs.)
Data Set (Inclusion of Outliers)
PMFI vs. Development Status
Undeveloped
Developing
Developing Private
Developed
11. 10
Funds: Based on the appearance of
school grounds and the quality of textbooks
and supplementary coursework available, the
amount of funds provided and effectively used
in schools increased with increasing
development.
Parents Involvement: A key complaint
found among students and teachers in
undeveloped areas was that parents in such
areas were rarely taking any role in the studies
of their child. It was actually seen that parents
tended to discourage attendance due to the
following: inefficiencies with RTE, need for
supervision of siblings, need to maintain
livestock, or the belief that the child’s time
would be better spent earning an income.
Peer Pressure: Another trend that
appeared was the inverse relationship between
absenteeism and development. Although not a
focus of this statistical analysis, the crude
number of students missing per class increased
as development decreased. Students not
regularly attending, however, were still good
friends of those who consistently attended the
local school. Just during the duration of this
study in the village areas, 8-10 different
accounts occurred of primary school students
previously seen in the school being found
playing or going from village to village
socializing with friends.
Student-Teacher Interactions: Severity
of student maltreatment appeared to increase
significantly when transitioning into an
undeveloped primary school. Upon asking
teachers to leave the class room, the primary
school students in undeveloped areas let out a
collective sigh of relief. When these students
began feeling more at ease and trusting, the
issue of maltreatment began arising. Teachers
were said to never bring enjoyment to the class.
Frightened looks were exchanged by students
when asked about long sticks that may be lying
on the teachers’ desks – a few timidly spoke up
after an extended silence saying the sticks were
for beating. Such items were rarely seen in the
other more developed schools and the
frequency of any maltreatment was much lower
in these schools.
MDM Service: Shortly following the
topics of maltreatment, the Mid-Day Meal was
said to not be served reliably. Although a few
teachers (and the Upsarpanch) indicated the
MDM had not been served for one month in
undeveloped areas due to issues with the
contracted distribution organization, students
reported otherwise. The students in both
primary schools of undeveloped areas (Murgi
Kheda and Sava Kheda) reported that the
MDM had actually not been served for 4
months. Children told their parents about these
issues, but the response many received was,
“let it go”. Only one parent brought up the issue
with any teacher or higher authority.
12. 11
PMFI versus Student Gender:
After computing the average PMFI-
value for each gender, the averages are further
broken down based on location and grade. This
comparison of gender differences across
location (all grades included) and grade (only
Ramad and Sava government schools included)
helps demonstrate the extent to which the
aspiration disparity between males and females
in schools exists [“Figure 4”]. The conducted
student t-test between the (modified) overall
PMFI-values of males and females resulted in a
p-value of 5.537 x 10-21, which shows a very
highly statistically significant difference in
aspiration level between rural student genders.
In the schools, there is evident and
strong gender discrimination in place.
Regardless of social norms, females in the class
are not being taught to by the teachers – many
times simply being left alone on one side of the
class as the teacher discusses the lesson with
the male side of the room.
0
1
2
3
4
5
6
7
8
Murgi Kheda Sava Kheda Ramad Ramad
Private
Sava
PMFI(LakhRs.)
Location
PMFI versus Gender|Location
(Unmodified)
0
0.5
1
1.5
2
2.5
3
3.5
4
Murgi Kheda Sava Kheda Ramad Ramad
Private
Sava
PMFI(LakhRs.)
Location
PMFI versus Gender|Location
(Modified)
0
2
4
6
8
10
12
14
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade
PMFI versus Gender|Grade
(Unmodified)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
3rd 5th 8th 9thPMFI(LakhRs.)
Grade
PMFI versus Gender|Grade
(Modified)
0
1
2
3
4
5
6
Unmodified Modified
PMFI(LakhRs.)
Data Set (Inclusion of Outliers)
PMFI versus Gender
Male Female
Figure 4: In the above four plots, the gender PMFI-
values are broken down with regards to both location
(left column) and grade (right column). Unmodified
and modified data set analyses have been conducted
and plotted. The “PMFI versus Gender” plot on the
left displays the overall difference in aspirations
between genders. This analysis includes all 203
students interviewed over the course of this study.
The unmodified and modified p-values found were
2.537 x 10-42 and 5.537 x 10-21 respectively.
13. 12
R² = 0.0312
0
0.5
1
1.5
2
2.5
3
3.5
0 0.5 1 1.5 2
PMFI(LakhRs.)
Parents' Estimated Income (Lakh Rs.)
PMFI versus Parents Income
(Modified)
Figure 5: Linear regression between student
PMFI and the corresponding parents’ estimated
income. 14 points plotted. R2-value = 0.0312
Discrimination is also prevalent among
parents, in that they tend to pull daughters out
of school for factors, such as those discussed
before (i.e. sibling and livestock supervision).
An example of this can be seen through the
struggles of one 11th grade boy in Sava.
Mukesh has been a diligent student from
his youth. He is the oldest of three, with two
younger sisters in 8th and 9th grade.
Surprisingly, however, the younger of the
sisters is in 9th grade and the older is in 8th.
Mukesh sees the talents of his youngest sister,
especially, and strongly wants them to continue
their education. Filled with sadness and anger,
he is left helpless as his parents are forcing his
sisters out of education for marriage in the next
two months – after completing, what is now,
their last year in school. Mukesh revealed some
of his deep frustration by saying, “Parents [in
India] don’t value education for girls. They take
decisions like this without even listening to me!
My parents are too close minded!”
Even among the students, there is an
acceptance of gender discrimination. This can
be seen through some of the quotes taken from
students in the classroom discussions:
“[Boys] are the ones who will be working
– why is her education so important?”
“Girls do not need to come to school,
they should be doing the house chores”
“5th grade is when girls stop coming…
after that, girls need to start getting
ready for marriage.”
Such trends can be seen in the data as
well. Interestingly, even the data’s outliers
indicate another aspect of how gender
discrimination manifests. All of the individuals
who are considered outliers were males. This is
to show that only the males observed were
aspiring to those occupations that were very
difficult to obtain even with high skill sets.
PMFI versus Parents Occupation:
Before analyzing the PMFI relationship
to parents’ occupation, the estimated average
income of each group of parents (separated by
location and grade of child) had to be derived.
Following this, child PMFI was plotted against
the corresponding estimated parents’ income
across all grades and locations observed (14
total combinations), as seen in “Figure 5”.
Calculated r2-values are also displayed along
with the linear regression on each scatter plot.
Supplementing these graphs are distinct
observations only made in the most
undeveloped village, Murgi Kheda. Particularly
of interest, the 3rd grade students of the
14. 13
primary government school in this area. Only
here was it found that more than half (10 of 17)
students desire to become farmers. In addition,
about one quarter (4 of 17) of the students
aspire to become laborers. Observed in
multiple areas, and most prevalently in Murgi
Kheda, a significant number of individuals left
school before reaching 5th grade.
Within Murgi Kheda, entire families
were comprised of individuals who did not
complete the 3rd grade. Major complaints were
either that their parents fell ill (child then
needed to supervise household), or they were
beat by their primary school teacher.
Lack of parent supervision, was also
cited as a significant contributor of hampered
primary schooling. Parents with laboring jobs
were frequently out of the house and could not
make sure their child is attending school
regularly. Also, since parents are often not
available at home, maintenance of livestock
and siblings tends to become a responsibility of
the children. It was primarily these reports that
most frequently pulled and pushed students
out of school.
Another issue that came up later in
several interviews with parents was that they
felt like they didn’t have the right to question
odd or inappropriate activities within the
village because they had a “lesser” career. Such
complexes were effectively detracting from
parental influences. Parents’ occupation, in
many cases, appeared to become a basis of a
family’s social and political empowerment.
Government and NGOs:
Swachchh Project: The allocation of
maximum 5 crores per year to the local
Panchayat has been reported to be severely
abused. Panchayat members, including the
Upsarpanch of Ramad has been accused on
several accounts for setting aside 2 of the 5
crores given for personal expenses and for
bribing educated individuals who threaten to
report him. Also, the School Management
Committee (SMC) that is said to be formed for
each school is not present in any legitimate
manner. Students, who are said to be delegated
the position as student representative by the
headmaster, had never heard of such a
committee. Only two parents who were talked
with indicated any participation in any “SMC-
like” committee.
RTE: Several individuals have strongly
expressed that this government policy is only
becoming part of the problem, and not the
solution. Parents have the belief that their child
will now learn nothing in the schools, simply
being passed through the grades so he/she can
fail in 9th grade. This worry is supported by the
stories of an increasing number of individuals,
such as the boy who failed 9th grade twice. Also,
coincidentally, the number of days in
attendance needed to be passed to the next
grade is equal to the number of days of
examinations during the school year.
MDM: Irregular and inadequate mid-
day meal distribution has been a major
downfall of the MDM initiative. Meals have
15. 14
been reported to have been and continue to be
absent for the past 4-5 months in areas like
Murgi Kheda. The food resources have been
allegedly misused by teachers, who upon
receiving the MDM for the children, will keep a
portion, if not all, of the food stuffs as to be
sold to local stores.
RTI: The government’s attempt to
increase its transparency has not been working
effectively due to three frequently seen issues:
lack of knowledge about the service, non-
disclosure of RTI by the panchayat, and
disempowerment of the village’s educated
peoples.
NGOs (GMKS): Efforts of NGOs, such as
Gandhi Manav Kalyan Society, have been
falling to the wayside due to two factors:
disempowerment of the organization, and
insufficient fund allocation and follow-through
for projects. Although present in the areas of
Ramad, Sava, and Murgi Kheda for several
years, GMKS fieldworkers reported feeling
unable to effectively work due to neglect of the
villagers and insufficient support from the local
governance structure. This is compounded with
the lack of adequate funds for large projects
and quickly changing projects leaves
fieldworkers and villagers in a state of “limbo”
without any fixed mission or goal of the
organization. Over time, this has led to
complacency among villagers, and even
fieldworkers, about the important issues being
tackled by NGOs, like GMKS.
Discussion
After putting forth the information
derived from statistical analysis of the data,
supplemented with bits of anecdotal evidence
provided through the interviews of students,
parents, government officials and NGO
fieldworkers, the following section will
consolidate the various aspects investigated
into a multi-faceted dynamic of key trends
found in the aspirations of rural children.
Grade, RTE, and Teacher Accountability:
Seen through the data analysis provided
[“Figure 1”], there is a decrease in aspirations
between 8th and 9th grade. Although the
discrepancy is not statistically significant at the
standard 95% confidence interval, the p-value
(0.143256) for this aspiration difference is still
quite low. Also noticed was a gradual increase
in aspirations from primary to secondary
schooling, with aspiration levels peaking at 8th
grade.
The peculiarity with these trends is
revealed after overlaying them with the RTE
scheme. If students are able to simply attend
the examination days (45 days per year), they
will fulfill the RTE attendance requirement and
will, therefore, be passed to the next class. With
the education system being so easy to
overcome until 8th grade, it is logical to see an
increasing sense in confidence and aspiration
between 3rd and 8th grade. However, when
faced with 9th grade examinations, the
realization seems to soon set in that school is
16. 15
actually more difficult than it used to seem.
Confidence levels soon begin to decrease, and it
soon follows that student aspirations will begin
to decrease as well.
On a surface level, it can quickly be
noted that the RTE scheme, itself, is the culprit
behind these observed trends. But, digging
deeper into the issue, it can be seen that
teacher accountability plays a critical part in
propagating these aspiration dynamics.
At the end of each day, the schools in
rural areas need to closed and locked up in
order to keep out unwanted animals that roam
in the night. This practice requires that the
school doors must be re-opened for classes to
proceed the following day. Even with 3 teachers
on staff, however, most (if not all) do not come
to the school regularly, and thereby leave
dozens of children loitering outside the school
premises for significantly large portions of the
school year. Students then begin to lose
interest in school and turn to recreation,
grazing of livestock, or labor. Even when the
teacher does decide to return to school, there is
no effort to ensure that children, too, come
back to receive what education they can.
When those select few students who are
motivated enough to persistently come to the
school gates each day luckily catch the school
open, they are faced with understaffed
classrooms (often sharing a teacher with one,
two or three other grades), sex discrimination,
and beating in the classes on a daily basis.
Like PMFI-values, Teacher staffing also
seems to follow a trend with both grade and the
RTE scheme layout. In the schools of Marad
and Sava (where 3rd, 5th, 8th, and 9th grade were
observed), teacher staffing was lowest for 3rd
grade. In all 3rd grade classes, the students
were taught alongside 1st and 2nd grade
students by 1 teacher. Once in 5th, students
tended to have more interaction with the
teacher since they were only taught alongside
4th grade students. 8th and 9th grade classes
were taught separately in both schools.
However, due to the apparent pitfalls of the
RTE scheme, students in the 9th grade often
complained that not enough teacher
involvement and support. This seems to be due
to the information gap (which resulted from
improper primary education) that many 9th
grade students are being forced to stressfully
span in one school year, or risk being failed.
Current preventive measures are based
off of exam performances halfway through the
year, but are only implemented during the last
two months of school. Putting into place, what
is basically a rushed cram-session for those
needing help is not provide students the
necessary time to understand and digest the
information they are learning. Especially if the
student does not have a solid foundation, such
a task would be increasingly difficult. Teachers,
therefore, need to increase focus on 9th grade
students suffering from the knowledge
discrepancies being systematically formed by
the RTE scheme.
17. 16
Many teachers interviewed do not seem
to notice the magnitude to which their students
look up to them for support. Students indicated
that they often saw their teachers as role
models. But if teachers are not attending the
schools or teaching appropriately, not only are
the students not receiving a proper education,
but they are also missing out on a crucial
opportunity for aspiration development.
Such issues of teacher absenteeism and
irresponsibility, in combination with certain
parent occupation trends, were observed in
severely undeveloped areas, such as Murgi
Kheda and Sava Kheda.
Parent Occupations in Undeveloped Areas:
Although parent occupation and income
was seen to have a very weak correlation with
their children’s aspiration level [“Figure 5”],
the interplay between occupation and
development helps make this connection a bit
stronger.
In the undeveloped areas, especially that
of Murgi Kheda, a large majority of parents has
occupations as farmers or laborers. It was
observed in both Murgi Kheda and Sava Kheda
that these areas had the highest proportions of
laborers. When looking at the PMFI-values of
students based on development status of their
area [“Figure 3”], the modified data showed
that most living conditions had fairly even
PMFI-values, but the “Undeveloped” category
was much lower. In fact, the difference between
undeveloped PMFI-values and those of more
developed areas was strongly statistically
significant with a p-value of 0.00262. Even
though development and occupations in an
area are related, the data is indicating
occupation income itself is not correlated to
child aspirations. How is the nature of these
undeveloped areas (and corresponding
occupations) affecting child PMFI-values to
yield the statistically significant differences
observed?
Since the majority of parents are
farmers or laborers in the undeveloped areas,
and these occupations require a significant
amount of physical work and travel, parents
tend to not be available at home during the day
for child supervising. It was seen that some
parents in undeveloped areas would send their
young children to school for 1st and 2nd grade
simply because they were unable to look after
them at school. Parents, however, generally
allowed the child to continue his/her primary
education as long as the child wanted to.
This system works well as long as the
conditions in the school are desirable for a
child. As teacher reliability continues to be low,
students in undeveloped areas keep shying
away from school. Students’ repulsion from
schools in 1st and 2nd grade is to the extent that
parents will drop the child off at school on the
way to a labor site, but the child will simply
leave as soon as the parents have departed.
Once students are no longer being pushed by
their parents after 1st and 2nd grade, many
18. 17
children’s attendance rates drop significantly,
given they don’t simply drop out of school.
At this point, the child is of 3rd grade age
(around 8 years old), and is left unsupervised.
If issues with teachers such as beating and
mistreatment of students continue, students
will shy away from schools even more than
before. As the teacher loses value as a role
model of sorts, the next individual to become
highly influential in the child’s life is his/her
parents and the community leaders. Now,
instead of school, the child begins doing
household chores, livestock maintenance, and
labor. From this, it can be observed that 3rd
grade children of undeveloped areas have
aspirations that tend towards the occupations
currently being held by their parents. Because
many adults have laboring and farming jobs in
undeveloped areas, it can be seen how primary
school children of such areas have significantly
lower aspirations than any other primary
school children observed.
Private Schools and Aspiration:
Shifting away from the undeveloped
areas, a sharp contrast in schooling and
aspiration development can be seen with the
private school of Ramad.
Parent and teacher involvement in the
child’s education was one key distinguishing
factor. Several parents indicated that they
would make sure their child would receive at
least an 8th-12th grade education. “I won’t push
my child to attend if they go on their own, but
they must complete up through secondary
school”. Parents frequently appeared at the
school during the times of interviews to check
on the class or consult the teachers. Teachers,
too, were comparatively very engaging. Plans
are currently in action to actually increase the
material being taught at Ramad’s private
primary school because the government
curriculum is “not encompassing enough”. This
clear difference in proactivity is accompanied
by an increase in funding due to annual
attendance costs. Funds were used for
maintenance costs and salaries, in addition to
providing supplementary course materials to
the students. Relatively extensive efforts in this
school to formally log all activities, attendance,
and student performance were taken through
the purchase of a computer and employment of
a record keeper.
With this being said, the PMFIs found
for the private primary school children were
not statistically significantly different than
those of government school children [“Figure
2”]. Where the private and government schools
see their differences are primarily in regards to
depth of education, attendance and
accountability of teachers, and greater
retention of students.
Due to these factors, children in private
schools can be seen to possess an accelerated
education in topics ranging from English to the
sciences – an advantage that may have
19. 18
significant effects on further education and life
outcomes.
Gender and Aspiration Development:
With a total of 203 students interviewed
(116 boys and 87 girls) from various
development areas and schooling conditions,
the data could be broken down in several ways.
With regards to gender, the data was analyzed
in three different ways, testing gender-based
aspiration differences across grade and
location of residence and an overall male-
female comparison [“Figure 4”].
What is seen across all factors is a very
clear discrepancy in female aspirations, relative
to those of males. In all of further
categorizations of students (gender given
grade, or location), females never held a
average PMFI-value greater than that of males
in the same school or area. This discrepancy is
most statistically significant found of the
analyses conducted (p-value = 5.537 x 10-21).
Just below the surface of these statistics
is the looming issues of gender discrimination
and the widespread mistreatment of women in
rural society. In undeveloped areas, teachers
would rarely attend school, let alone effectively
teach students. But compounding these
negative contributors to child aspiration
development is the marginalization of female
students in schools of all development levels.
The views of gender discrimination were
found to be so heavily engrained in the society
that individuals of all ages and backgrounds
shared the ideology. From a young age, female
students are being told they cannot be better or
more influential than a socially determined
maximum. Teachers frequently ignore or set
aside female students when lecturing a class.
As this practice is initiated in the early stages of
schooling, females grow to have an acceptance
of this social norm. Such trends are seen to
emerge as early as 5th grade in which girls,
instead of sitting the front of the class, will tend
to seat themselves along the far walls or in the
corners of the rooms.
Parents play an important role in
propagating such behaviors from one
generation to the next. Often victims of gender
discrimination themselves, mothers are
primary the role models for their daughters. If
the home, itself, is allowing these ideologies
continue, daughters are raised to become
disempowered even before attending the first
day of primary school.
Female students are in many cases not
even allowed to attend school (as seen with
Mukesh’s sisters), just because they have
reached the marriage-age. Women who are
showing extraordinary intellectual skills in
schools or have an earnest desire to learn not
only limited by a “glass ceiling”, but are also
continuously hampered by the burden of
gender discrimination.
20. 19
Government and NGOs:
Local government officials and leaders
are found to be among the most empowered
individuals in the rural society. The inequity in
authority is ever increasing with programs such
as the “Swachchh” project. Providing funds of
the size being directly given to local panchayats
is allocating too much power to these local
governance structures (that previously didn’t
have such authority) over too short of a time
period. The promise of these 5 crore funds
along with insufficient regulation and
monitoring of fund expenditures only catalyzes
the forms of exploitation seen.
Government has effectively added the
“Swachchh” project to its arsenal of polices, but
the key public service and transparency policies
such as MDM, RTE, and RTI have fallen short.
Disempowerment of individuals due to
stigmatized occupation, caste, and gender only
allow these issues to continue. Lack of action
on the part of higher government officials to
responsibly supervise panchayat activities sets
the stage for local officials to not disclose
information about government policies to the
village. In this way, the lack of supervision and
follow through on the part of government and
non-government organizations facilitates the
formation of micro-policy environments in
which the local government has chosen and
removed national and state laws as seen fit.
This state of unrest only prolongs effective
treatment of detrimental factors contributing
to child aspirations from occurring.
Conclusion
Over the course of this study, a total of 7
factors were investigated among the children of
4 distinct rural areas. Analyses of collected data
have been put forth and discussed with the
successful implementation of “Predicted
Maximum Future Income” (PMFI) – an
income based estimator for child aspirations. A
combination of student t-tests and linear
regression analyses were used to view
quantitative trends that were present in the
data. Each set of statistical results were then
compared to anecdotal evidence which was
collected through the interviews and
discussions with children, parents, teachers,
NGO fieldworkers, and government officials.
Following this comparison, it can be
seen that all of the trends and discrepancies
seen in the data are substantiated by the stories
and experiences of the 300+ rural individuals
interviewed.
First, the child aspirations seen in each
grade were closely related to the pitfalls and
loopholes of the Right to Education scheme.
Increased accountability of school teachers
with regards to absenteeism, along with
uniform progress checks for students, would
effectively reduce the failure rates of students
observed in the 9th grade of both Ramad and
Sava.
Second, the reported differences
between private and government institutions
were not seen to effect children’s aspirations in
21. 20
the early years of schooling. Instead, these
factors (such as parent-teacher involvement,
and fund availability), played a significant role
in the education of the individuals. For this
reason, it is concluded that private primary
schools do not have a significant advantage
over government primary schools regarding
children’s aspiration development.
Third, an interesting dynamic emerged
between aspiration, parents’ occupation, and
development status. The combination of travel-
intensive occupations, severe under-
development, and inadequate monitoring of
government schools leads to a dramatically
decreased level of child aspirations. Individuals
of these backgrounds should be in the forefront
of government and NGO efforts to stimulate
their educational and societal deficiencies.
Strict regulation of teachers’ attendance and
student mistreatment are keys to keeping
children of these conditions in schools.
And finally, perhaps the most
influential widespread factor for students’
aspirations is gender inequality. Female
students are being restricted from the same
quality of education as male students,
regardless of intellectual prowess or drive.
Gender discrimination in and out of schools
single-handedly curtails the aspirations of
42.9% of students (87/203) across all ages,
grades, and levels of rural development. In
order for aspirations to be thoroughly
stimulated in rural children, the biggest
improvement in child aspirations will occur
once gender inequality is reduced in rural
societies.
Future Studies and Suggestions:
First and foremost, an essential
improvement for future related studies would
be to increase the time and manpower available
to researchers for conducting interviews.
Although encompassing, classroom setting
discussions require greater discipline of the
students and can give rise to group think, in
which individuals of the same group will
converge on one response for uniformity within
the group. Increased resources as mentioned,
would allow for group discussions to be
followed up with one-on-one interviews of
students.
Also, if this study were to be carried out
with more schools, students and higher grades,
the differences observed may become more
statistically, while also taking into account a
more diverse set of backgrounds.
Studies unable to be conducted, but
would be of interest in the future, include:
Analyzing aspiration trends of private
school students through education in
secondary schools and college.
An occupation-by-occupation influence
analysis on children’s aspirations and
educational prospects.
Cross-community analysis of women’s
empowerment and aspirations.
22. 21
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23. 22
Appendix A – PMFI Occupation Median Incomes
Used for computing the PMFI-values in each of the analyses conducted as well as for estimating
parents incomes for particular groups of interest.
Occupation Median Income
Secondary School Teacher 198,804
General Doctor 473,902
Software Engineer 609,327
Registered Nurse 148,642
Police Investigator 575,500
Police Officer 239,999
Headmaster 360,100
Driver 143,797
Cook 198,500
President 5,778,509
Air Force 729,277
Farmer 20,184
Military Soldier 700,000
Cricket Player 2,500,000
Store Owner 312,325
Labor (Manarega) 18,000
Tailor 150,600
Barber 96,000
Forest Officer 80000
Carpenter 216000
Bike Maker 126000
24. 23
Appendix B – Average PMFI-values Computed
PMFI values (un-/modified) shown are broken down across location, grade, and gender.
Location Grade
Gender
(n=?)
PMFI
PMFI w/o
High Incomes
(Modified)
Number of
Individuals
Removed
Madra 9th F 5 169098.4
Madra 9th M 13 285077.4615
Madra 8th F 6 182083.3333
Madra 8th M 19 352081.6842
Madra 5th F 2 173723
Madra 5th M 5 1457043.4 376677 -1
Madra 3rd F 5 168706.8
Madra 3rd M 0 N/A
Vaas 9th F 23 205277.913
Vaas 9th M 24 849418.125 299224.1667 -6
Vaas 8th F 18 214087.2222
Vaas 8th M 14 418396.7143
Vaas 5th F 5 198804
Vaas 5th M 1 473,902
Vaas 3rd F 4 148642
Vaas 3rd M 2 336353
Kukada Kheda 5th F 1 473902
Kukada Kheda 5th M 6 1188336.167 270301.6 -1
Kukada Kheda 3rd F 5 20184
Kukada Kheda 3rd M 12 64111
Vaas Kheda 5th F 2 198,804
Vaas Kheda 5th M 1 198,804
Vaas Kheda 3rd F 1 198,804
Vaas Kheda 3rd M 3 198,804
Madra Private 5th F 3 226267.3333
Madra Private 5th M 3 239999
Madra Private 3rd F 7 191638
Madra Private 3rd M 13 223041.4615
25. 24
Appendix C – Numerical results of Grade Analysis
Units: Rupees
Grade
PFMI
(Unmodified)
PFMI
(Modified)
3rd 191891.6364 191891.6364
5th 700045 286015.2308
8th 306897.8246 306897.8246
9th 456291.1692 248456.3729
Student T-test: Difference Between 8th and 9th Grade
(One-tailed, unequal variance)
T-test (p=?) Modified T-test (p=?)
0.021034 0.143256
0
2
4
6
8
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade in Government School
PMFI vs. Grade (Unmodified)
RTE Ends
0
1
2
3
4
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade in Government School
PMFI vs. Grade (Modified)
RTE Ends
26. 25
Appendix D – Numerical Results from Private School Analysis
Units: Rupees
Unmodified PMFI-values Modified PMFI-values
Grade Private School Government School Private School Government School
3rd 212,050 168,707 212,050 168,707
5th 233,133 1,090,380 233133.1667 309,026
Overall 216,916 706,350 216915.5385 245,244
Student T-test: Difference Between Private and Government School
(One-tailed, unequal variance)
T-test (p=?) Modified T-test (p=?)
0.156395908 0.253681624
0
20
40
60
80
100
120
Private School Government School
PMFI(LakhRs.)
School Type
PMFI vs. School Type (Unmodified)
3rd
5th Unmodified
Overall
0
1
1
2
2
3
3
4
Private School Government School
PMFI(LakhRs.)
School Type
PMFI vs. School Type (Modified)
3rd
5th Modified
Overall Modified
27. 26
Appendix E – Numerical Results from Development Level Analysis
Units: Rupees
PMFI vs. Development Area (3rd/5th grades)
Development Status Unmodified Modified
Undeveloped 318251.5806 136243
Developing 706349.75 245244.3636
Developing Private 216915.5384 216915.5385
Developed 227933 227933
Student T-test: Difference Between Undeveloped and More Developed Areas
(One-tailed, unequal variance)
T-test (p=?) Modified T-test (p=?)
0.315517893 0.002618387
0
1
2
3
4
5
6
7
8
Unmodified Modified
PMFI(LakhRs.)
Data Set (Inclusion of Outliers)
PMFI vs. Development Status
Undeveloped
Developing
Developing Private
Developed
28. 27
Appendix F – Numerical Results from Gender Analysis
Units: Rupees
Unmodified Data Modified Data
PMFI vs. Gender given Location
Location Male Female Male Female
Murgi Kheda 438852.7222 95803.66667 124755.2941 95803.66667
Sava Kheda 198804 198804 198804 198804
Ramad 477858.8108 173831.7778 330618.5278 173831.7778
Ramad Private 226221 202026.8 226221 202026.8
Sava 668053.5854 203271 354005.6286 203271
PMFI vs. Gender given Grade (Ramad and Sava Govt. School)
Grade Male Female Male Female
3rd 336353 159789.1111 336353 159789.1111
5th 1293186.5 191638 396122 191638
8th 380215.3333 206086.25 380215.3333 206086.25
9th 651136.2703 198817.2857 293291.6774 198817.2857
PMFI vs. Gender Overall
Male Female T-Test (p=?)
Unmodified 494698.9138 189471.5402 2.53703 x 10-42
Modified 285444.963 189471.5402 5.53728 x 10-21
0
1
2
3
4
5
6
7
8
Murgi Kheda Sava Kheda Ramad Ramad
Private
Sava
PMFI(LakhRs.)
Location
PMFI versus Gender|Location
(Unmodified)
0
2
4
6
8
10
12
14
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade
PMFI versus Gender|Grade
(Unmodified)
29. 28
Appendix F – Continued
0
0.5
1
1.5
2
2.5
3
3.5
4
Murgi Kheda Sava Kheda Ramad Ramad
Private
Sava
PMFI(LakhRs.)
Location
PMFI versus Gender|Location
(Modified)
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
3rd 5th 8th 9th
PMFI(LakhRs.)
Grade
PMFI versus Gender|Grade
(Modified)
0
1
2
3
4
5
6
Unmodified Modified
PMFI(LakhRs.)
Data Set (Inclusion of Outliers)
PMFI versus Gender
Male Female
