Relationship Between Income and Education

7/31/2019 Relationship Between Income and Education

http://slidepdf.com/reader/full/relationship-between-income-and-education 1/34

Submitte

ASSIGNMENT RELATI

To | Mr. Zeeshan Arsh

ONSHIP BETWEEN INCOME &

6/25/2012

d

EDUCATION



G

Gohar Ejaz

Waqas Afzal

Usman Nadeem

Bilal Ahmed

Shoaib Arshad B

OUP MEMBERS

11014220-

11014220-

11014220-

11014220-

tt 11014220-

2

27

19

18

33

26



3

Dedicate

To

Our

Parents



4

Table Of Contents

Details Page #

Abstract ……………………………………………… 5

Introduction …………………………………………… 8

Variables ……………………………………………… 10

Graphs ……………………………………………… 11

Scatter diagram …………………………………………… 12

Literature review ……………………………………… 16

Methodology …………………………………………… 18

Framework …………………………………………… 22

Conclusion …………………………………………… 28

References …………………………………………… 30



5

Ch # 00

Abstract



6

Abstract

Education plays important role in the development of the country. We checked that the

relationship of the income towards education. We collect data for male and female from UOG

without any discrimination through questionnaires. We take income as independent variable and

education as dependent variable. We apply regression line on the data and check the efficiency of

the data. Then we comparison two discipline, first is MBA and second is M.COM. We find

regression line, standard error, and coefficient of determination of the data. With the help of this

we checked that the fitness and consistency of the model. We read different literatures.



I

Ch # 01

troduction

7



8

Introduction

The topic of our research is “the relationship between income and education”. Let me tell you the

importance of the education then you will know that how education change income. Education is

a social instrument through which man can guide his destiny and shape his future. An

uneducated man cannot become a part of development. Islam makes it compulsory for every man

and woman to get education. In the modern age, nations desirous of progress spend huge

amounts on education. Education occupies a fundamental place in the development of a country.

No human being is able to survive properly without education. Education tells men how to think,

how to work, and how to make decisions.

Know we have clear idea about importance of education. We collect data through questionnairesfrom “university of gujrat” and put into process.

Our object is to check the relationship between income and education. We also check the

consistency between variables. With the help of this we will be able to check that the fitness or

consistency of the model.

We collect data from books regarding the methodology. We collect data for male and female

without any discrimination. We also read literatures of different writers. And use internet to get

some help. We also randomly ask form different age group peoples about the spending of the

income at education. The data we used from internet, his time period is 19-june-2012 to 24-june-

2012 (references mentioned).

We read literatures of different writers. ( Husain 2005) education increases the efficiency of the

labor and skills. ( Nasir and Nazli 2000) education increase household living. ( Memon, Farooq

and Ashraf 2010) education provides leadership role. And take part in development. And also

develop the social, poetical, and cultural life. We are agree with their, because education plays an

important role in a society. We do our work differently. We apply regression line on the data and

check that the fitness and consistency of the data.





10

Variables

Two variables are used one is dependent and second is independent.

Independent variable = Income = X

Dependent variable = spending at Education = Y

X Y

20 5.80

30 12.0030 5.20

30 5.00

85 21.00

25 5.45

20 5.20

30 10.00

40 5.50

150 15.00

30 10.00

30 6.50

25 6.0060 17.00

35 6.00

45 5.70

50 5.60

30 10.00

100 10.00

100 9.00

100 30.00

70 13.00

38 10.00

20 19.0031 18.00

Note: take 1000 as common for both.



0

20

40

60

80

100

120

140

160

1 2 3 4 5 6 7 8 9 10

0

20

40

60

80100

120

140

160

1 2 3 4 5 6 7 8

-

5.00

10.00

15.00

20.00

25.00

30.0035.00

1 2 3 4 5 6 7 8

-

5.

10

15

20

25

30

35

11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

X = Income

Y = spending at education

Both (X & Y)

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

11

0

.00

.00

.00

.00

.00

.00

Series1

Series2

Series1

Series1



-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

- 20,000 40,000 6

A x i s T i t l e

y = 0.0894x + 6261.6

R² = 0.2241

,000 80,000 100,000 120,000 140,000 160,000

Axis Title

Scater Diagram

12

Series1

Linear (Series1)



-

50,000

100,000

150,000

200,000

1 2 3 4 5 6

-

20,000

40,000

60,000

80,000100,000

120,000

140,000

160,000

1 2

sr # D

1

2

3

4

5

6

Series1

-

5,000

10,000

15,000

20,000

1 2 3 4 5 6

-

5,000

10,00

15,00

20,00

3 4 5 6

M.com Data

epartment Income Edu

M.COM 30,000 10,000

M.COM 150,000 15,000

M.COM 40,000 5,500

M.COM 30,000 10,000

M.COM 60,000 17,000

M.COM 70,000 13,000

13

Series1

0

0

0

Series1

Series2

ation



-

20,000

40,000

60,000

80,000

100,000

120,000

1 2 3 4 5 6 7

-

20,000

40,000

60,000

80,000

100,000

120,000

1 2 3

sr #

1

2

3

4

5

6

7

Series1

-

10,000

20,000

30,000

40,000

1 2 3 4 5 6 7

-

5,000

10,00

15,00

20,00

25,00

30,00

35,00

4 5 6 7

MBA Data

epartment Income Educ

MBA 30,000 12,000

MBA 100,000 9,000

MBA 25,000 6,000

MBA 30,000 10,000

MBA 100,000 10,000

MBA 85,000 21,000

MBA 100,000 30,000

14

Series1

Series1

Series2

tion



Lit

Ch # 03

rature review

15



16

Literature review

( Memon, Farooq and Ashraf 2010) The education provides a leadership role in the society. The

citizens of the country develop through education institutes and develop physically, mentally

socially and religiously. It improves and promotes the economic social, political and cultural life

of the nation.

( Shahrukh R. 1991) Pakistan is lacking behind the south Asian countries in both the educational

achievement and the distribution of resources for education. Higher education recently increased

the distribution of income among the households.

( Parvez 2011) Pakistan economy is not stable that results in increasing the dropout rates becauseof household’s income. It results in higher cost that would limit the access of education to the

children of the low income household groups. There should be expansion the campuses and

universities in the underdeveloped areas and supports to the needy students.

( Salim, Fayyaz 2006 ) The nation represents the development through the standards of education

system. Education is not only for knowledge but also relates to the societies beliefs and norms.

Education represent the past, present and future of the nation. The failure of student increase the

crimes and ignoring the moral values of the society.

( Nasir and Nazli 2000) The education has a positive and significant role on illiteracy and

increases the returns of household living in Pakistan.

( Husain 2005) Education will rise the efficiency of the labor force and develop the skills which

gives comparative advantage to them.



Ch # 04

ethodology

17



18

0

5

10

15

20

25

1 2 3 4 5 6 7 8 9 10 11 12

Series1

Methodology

Regression:

Sir Francis Galton (1822 – 1911) an English biometrician introduced the term regression in

1885. Regression analysis is a mathematical measure of the average relationship between two or

more variables in term of the original units of the data the relationship between one dependent

and more than one independent variable is called regression.

Regression equation:

In regression equation of Y and X, we take Y as dependent variable and X as independent

variable through this equation. This equation is given under.

Y = a + bX

a= Y- intercept when X=0

b= regression coefficient Y on X (Slope of line)

Slope of line (b):

Shows that the average rate of change in Y against a unit change in X. change with respect to

time. “b” indicates the change in Y for a one unit change in X is called slope of line.

The slope of line tells us how something change over time. If we find the rate of slope we can

find the rate of change over that period.

Y= a + bX



19

Dependent variable (Education):

The variable whose resulting value depends upon the selected value of the independent variable

is called dependent variable. It is also known as the predicated variable or explained variable.

Education:

Education is merely the delivering of knowledge skills and information from teachers or

professionals to students or learner.

Importance of Education:

Education is a social instrument through which man can guide his destiny and shape his future.An uneducated man cannot become a part of development. Islam makes it compulsory for every

man and woman to get education. In the modern age, nations desirous of progress spend huge

amounts on education. Education occupies a fundamental place in the development of a country.

No human being is able to survive properly without education. Education tells men how to think,

how to work, and how to make decisions.

Independent variable (Income):

The variable that provides the basis for estimation is called independent variable. It is also

known as the predicator variable or explanatory variable.

Income:

The amount of money or its equalent received period of time in exchange for labor and services

for the sake of goods and property or as profit from financial investment.

Importance of Income:

Income is important because, we can afford the things which we desire, such as paying rent,

bills, other bills like for food, water that we consume.



20

Standard error (S.E.):

The standard error is the estimated standard deviation or measure of variability in the sampling

distribution of a statistic.

The S.E. depends upon three factors.

N = the number of the observation in population.

n = the number of the observation in sample.

The way that the random sample is chosen.

Coefficient of determination (r²):

It is denoted by r ². The Coefficient of determination is a measure of the variance of predictedoutcome with a value of 0 and 1.it is calculated the square of correlation coefficient (r) between

the simple and predicted data.



Ch # 05

rame Work

21



22

Frame Work

Note: take 1000 as common for both.

sr # Department Income Education X Y x² y² xy

1 BBA 20,000 5,800 20 5.80 400 33.64 116.00

2 MBA 30,000 12,000 30 12.00 900 144.00 360.00

3 BBA 30,000 5,200 30 5.20 900 27.04 156.00

4 BBA 30,000 5,000 30 5.00 900 25.00 150.00

5 MBA 85,000 21,000 85 21.00 7,225 441.00 1,785.00

6 BBA 25,000 5,450 25 5.45 625 29.70 136.25

7 BBA 20,000 5,200 20 5.20 400 27.04 104.00

8 M.COM 30,000 10,000 30 10.00 900 100.00 300.00

9 M.COM 40,000 5,500 40 5.50 1,600 30.25 220.00

10 M.COM 150,000 15,000 150 15.00 22,500 225.00 2,250.00

11 M.COM 30,000 10,000 30 10.00 900 100.00 300.00

12 B.COM 30,000 6,500 30 6.50 900 42.25 195.00

13 MBA 25,000 6,000 25 6.00 625 36.00 150.00

14 M.COM 60,000 17,000 60 17.00 3,600 289.00 1,020.00

15 B.COM 35,000 6,000 35 6.00 1,225 36.00 210.00

16 B.COM 45,000 5,700 45 5.70 2,025 32.49 256.50

17 B.COM 50,000 5,600 50 5.60 2,500 31.36 280.00

18 MBA 30,000 10,000 30 10.00 900 100.00 300.00

19 MBA 100,000 10,000 100 10.00 10,000 100.00 1,000.00

20 MBA 100,000 9,000 100 9.00 10,000 81.00 900.00

21 MBA 100,000 30,000 100 30.00 10,000 900.00 3,000.00

22 M.COM 70,000 13,000 70 13.00 4,900 169.00 910.00

23 IT 38,000 10,000 38 10.00 1,444 100.00 380.00

24 IT 20,000 19,000 20 19.00 400 361.00 380.00

25 IT 31,000 18,000 31 18.00 961 324.00 558.00

TOTAL 1,224,000 265,950 1,224 265.95 86,730.00 3,784.77 15,416.75



23

Education and Income

Descriptive Statistics

Mean Std. Deviation N

Education 10.6380 6.31003 25

Income 48.9600 33.41841 25

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square

Change F Change df1 df2 Sig. F Change

1 .473a

.224 .190 5.67772 .224 6.643 1 23 .017

a. Predictors: (Constant), Income

b. Dependent Variable: Education



24

Coefficients

Model

Unstandardized

Coefficients

Standard

ized

Coefficie

nts

t Sig.

95% Confidence

Interval for B Correlations

Collinearity

Statistics

B

Std.

Error Beta

Lower

Bound

Upper

Bound

Zero-

order Partial Part

Tolera

nce VIF

1 (Const

ant) 6.262 2.043 3.065 .005 2.036 10.487

Income .089 .035 .473 2.577 .017 .018 .161 .473 .473 .473 1.000 1.000

a. Dependent Variable:

Education

Interpretations

• a = 6.262 is a positive intersect of simple regression line that represent the positive curve.

We can get it by putting x = 0 in a simple regression line.

• b = 0.089 is the positive slope of the simple regression line, the numerical value shows

that if there is a one unit change in x, therefore, it will be 0.089 units change in y in the

same direction.

•

r²= 0.22, this mean that only 22.4% of the variation in variable y is explained by thevariable x and remaining 77.6% is due to other factors.



25

MBA VS M.COM

Descriptive Statistics

Mean Std. Deviation N

Education 12.9615 6.65351 13

Income 65.3846 39.23548 13

Correlations

Education Income

Pearson Correlation Education 1.000 .472

Income .472 1.000

Sig. (1-tailed) Education . .052

Income .052 .

N Education 13 13

Income 13 13



26

Model Summaryb

Model R R Square

Adjusted R

Square

Std. Error of

the Estimate

Change Statistics

R Square

Change F Change df1 df2 Sig. F Change

1 .472a .223 .152 6.12764 .223 3.148 1 11 .104

a. Predictors: (Constant), Income

b. Dependent Variable: Education

Coefficients

Model

Unstandardized

Coefficients

Standardiz

ed

Coefficient

s

t Sig.

95% Confidence

Interval for B Correlations

Collinearity

Statistics

B Std. Error Beta

Lower

Bound

Upper

Bound

Zero-

order Partial Part

Toleran

ce VIF

1 (Consta

nt)7.731 3.403 2.272 .044 .242 15.220

Income .080 .045 .472 1.774 .104 -.019 .179 .472 .472 .472 1.000 1.000

a. Dependent Variable: Education



Ch # 06

onclusion

27



28

Conclusion

In this paper we find the relationship between household incomes and spending at education of at

one child. We took income as independent variable and education as dependent variable. We fit

regression line oat data to check the significance of the model and also check the fitness and

consistency of the model. We compare different disciplines. a is a positive interpreted and

representing the positive curve. b is a positive slope and the answer of regression coefficient

showed that if there is one unit change in x there for it will be 0.0894 unit change in y. we can

implement these results in future to check the consistency and variation of the data.



Ch # 07

eferences

29



30

References

Hussain, Nazir. (2009). Business mathematics & statistics. Azeem acadmy. (page # 145.)

Kamal, Dr Shahid, Choudary, Sher Muhammad. (2009). Introduction to statistical theory.

ILMI kitab khana.

Heitzman, W. R., & Mueller, F. W. (1980). Statistics for Business and Economics. Allyn

and Bacon.

Newbold, & Paul, N. (2008). Statistics For Business And Economics And Student Cd, 6/E

(With Cd). Pearson Education India.

Mansfield, E. (1994). Statistics for Business and Economics: Methods and Applications.

Norton.

Importance Of Education In Pakistan - Essays - Mohammaddanish. (n.d.). Retrieved June

22, 2012, from http://www.oppapers.com/essays/Importance-Of-Education-In-

Pakistan/749678

Slope and Rate of Change. (n.d.). Retrieved June 22, 2012, from http://www.algebra-

class.com/rate-of-change.html

Linear Equations. Formulas, Tutorials, and more. (n.d.). Retrieved June 22, 2012, from

http://www.mathwarehouse.com/algebra/linear_equation

Husain, I. (2005). Education, employment and economic development in Pakistan.

Education Reform in Pakistan: Building for the Future, 33–45.

Isani, U. A. G., & Virk, M. L. (2003). Higher Education in Pakistan. A Historical and

Futuristic Perspective). National Book Foundation, Islamabad . Retrieved from

http://prr.hec.gov.pk/Chapters/233-0.pdf

Khalid, S. M., & Khan, M. F. (2006). Pakistan: The state of education. The Muslim

World , 96 (2), 305–322.

Khan, A. H. (1997). Education in Pakistan: Fifty Years of Neglect. Pakistan

Development Review, 36 (4; PART 2), 647–665.

Khan, S. R. (1991a). Financing higher education in Pakistan. Higher Education, 21(2),

207–222. doi:10.1007/BF00137074





32

Ch # 8

Appendix

( Questionnaires )



Spending of income at

Dear participant,

This questionnaire is designed to

of the family)”. You are the on

experience your work. We willrespond to the questions honestl

Your information’s and response

research team will have access t

Thank you very much for your ti

ducation (only at one person of t

study “Spending of income at education (on

who can give us correct information’s and pi

lease if you will give correct information’s..

will keep highly confidential and secret. Only

the information you give.

me and cooperation.

33

e family)

y at one person

ture of how you

e request you to

embers of our



Questionnaires (Example)

1. What is your name?

_______Tayyab Saleem___________________.

2. What is your Age?

(Years) ___23____.

3. Gender:

a. Male.

b. Female.

4. In which discipline you are?

_________MBA________________

5. What is your father’s name?

___________M. Saleem_______________.

6. What is your father’s occupation?

a. Employed.

b. Businessman.

c. Teacher.

d. Other specific. ( _____________ ).

7. Area of residency?

a. Urban.

b. Rural.

8. What is your father’s income (monthly)?

Rs._________44000_______________.

9. Spending of income at education (monthly)?

Rs.__________13000______________.

Documents

Relationship Between Income and Education