College of naturaland computational science

As grade level in school increases the numb of female students starts to decline because of lots of factors, consequently higher education remains an area of learning from the fortunate

COLLEGE OF NATURAL AND COMPUTATIONAL SCIENCE DEPARTMENT OF STATISTICS

RESEARCH PROPOSAL ON STATISTICAL ANALYSIS ON FACTORS AFFECTING ACADEMIC ACHEIVMENT

OF FEMALE STUDENTS IN AMBO UNIVERSTIY IN THE CASE OF COLLEGE NATURAL AND(

COMPUTATIONAL SCIENCE)

GROUP MEMBERS

NAME ID NO

1 TAFESE ASHINE……….R/1668/05

2 SOLOMON DADI ……… R/1667/05

3 TOLEMARAM JALATA ……… R/1670/05

Table of Contents

Contents Page

CHAPTER ONE 1 Introduction ……… 1

1.1 Back ground of study ……….1

1.2 Statement of the problem ………2

1.3 Objective of the study ………3

1.4 Significance of the study ………3

CHAPTER TWO LITRATURE REVIEW 2.1 Study time ………4

2.2 Affirmative action ………5

CHAPTER THREE: METHODOLOGY 3.1 Description of the Study Area ……… 6

3.2 Data ……… 6

3.3 Study Design and Sampling Procedure ………6

3.4 Sample site Determination ………7

3.5 Method of Data Analysis ……….8

3.5.1 Variable Identification ……… 8

3.5.2 Statistical Model Identified Model ……… 9

3.5 3 Assumption of the Identified Model ……… 11

3.5.4 Assessment of fitting the Identified Model ……….12

4 Tentative work Plan ……… 13

5 Budget Breakdown ……… 14

6 REFERENCE ……… 15

CHAPTER ONE

1 INTRODUCTION

As the beginning of human history, the environment favored and promoted equality of males, however as the exposure of males natural environment differed various activities and dangers increased both sexes started to differ in the nature and depth of experience, since the gender disparity that began in this way was widened by religious, political, economic, culture and other factors The gender disparity that began in this way was widened by religious, political, economic, culture and other factors Currently gender differentiators are reflected in the accesses

to the three things of the world, political power, economic privileges and social and as well as cultural prestige (power 1975) Consequently females exposure’s to these things, their contributions to the world and their benefits from the accommodated wealth of the world are affected by many factors As a result the problem of gender disparity have now become both vicious and spiral to approach to alleviate these problem aggressive measures and integrated effects are required from all the concerned politicians and academician

Education is one of the social factors where by gender disparity is reflected In the field of education, the numbers of educated females are very low As grade level in school increases the numb of female students starts to decline because of lots of factors, consequently higher education remains an area of learning from the fortunate enough to join higher institutions are characterized by lower academic performance and higher forced with drawl Consequently such inequality in higher education representation has a serious lifelong impact on their opportunities

to participate in the country’s political power sharing, economic privilege as well as social representation This is because currently joining their higher education has become revenue to upward social mobility status, political power, economic privilege and social prestige Education

Assessment may be defined as nay method used to better understanding the current knowledge that student posse

This is implies that assessment can be simple teaching subjective judgment based on single observation of student achievement or as a complex as standardized test The idea of current knowledge implies that what students know are always changing and what we make judgments about the achievement through comparison over a period of time (field man 1990)

1.2 Statement of The Problem

The reason why the study was conducted to identify the following problems

What are the most factors that affect the academic achievement of female students? Does the academic achievement of female students depend on study methods?

Does the academic achievement of female student depend on the using of stimulant? What relationship has between class missing and CGPA of female students?

Does role of affirmative action have significance effect on the academic achievement of female students?

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1.3 OBJECTIVE OF STUDY

1.3.1 General Objective

The general objective of the study is to identify the factors that affect academic achievement of female students in Ambo University main campus

1.3.2 SPECIFIC OBJECTIVE

To investigate the effect of each factors

To identify the factor that highly affects the academic achievement of female students

To investigate why many female students are not successful in the university

To identify the relationship of CGPA of female students and each factors

1.4 SIGNIFICANCE OF THE STUDY

The study provided the correct information about the factors that affect academic achievement

of female students in the campus It realized significant effect of each factor for the concerned part and to serve output of the study as a tool for academic issue of education of the university

CHAPTER TWO

2 LITERATURE REVIEW

Education is the process by which the human beings transmit their experience, new findings and values accumulated over the years In this struggle for survival and developments through generation Education enables individuals and society to make all round participation in the development process by acquiring knowledge, ability, skills and attitudes It is one of the critical sources to the alleviation of poverty (miller, 1998)

Education is a “key stone” of the economic and social development It is concerned with the development of character and a key part of strategy to improve in dividable, well being and society’s economic and social development In addition education creates national unity, social and social cohesion by teaching common mores, ideologies and social ideas It has been indicated that education has a process involves the realization of certain individual and social ideas It has been verified through research that education increases the ability of farmers to think abstractly, which enables them to recognize to casual relationship between technologies and output Hence, in the overall development effort high priority should be given to education Education provides a way of life and occurs in many diverse ways (field man, 1990) 2.1 STUDY TIME

Time management skills are important to achieve in work Time management is defined as clusters of behavioral skill sets that are organization of study Time management skill including activities per formed by student such as planning prioritizing work, preparation themselves for examination and evaluation, and attending the schedule

In the study, time is operating the study to study in time by using time properly Time management in the study reflect through the number of time spend on education for study and working (Amitava Rock 2010)

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2.2 AFFIRMATIVE ACTION

Affirmative action in education provides grants and fellow ships, tutorial program and other unities that help minority and females achieve level of academic attainment were denied to them until very recently It is the program that has played critical role in opening up opportunities for females and minorities to being and to take the right ful place in over society Affirmative action

is very controversial issues that always cause great sensation and discussing among educators and politicians It is a term describing a series of orders, rules and procedures designed to protect minorities from discrimination in employment education and other surviveds It was start to combat the effect of historical discrimination that denied minorities equal to education opportunities The practice of affirmative action is an attempt to resolve the issue of discrimination Affirmative actron is proactive or the preferential treatment of persons in employment, the admission of persons in employment of the selective school and university and granting of other social goods and resource by giving positive consideration to specified race and ethnicities to be the one gender (Acquire A 200)

CHAPTER THREE

3 METHODOLOGY

3.1 Description of the Study Area

The study was conducted at Ambo University main campus It is one of the higher institutions which is located western shoa of Oromia It is created as agricultural college in 1939 It is situated about 114 km for from west of Addis Ababa Now a day, the University has two additional branches, namely Awaro and wolliso campus It is extended widely to reach the horizon of excellence

3.2 Data

For our study we used both primary and secondary method of data collection Primary data collection was used by designing and distributing questionnaire to the respondent and collection was used to have total number of female students from each batch of campus that is stored in the main registrar of the campus

3.3 Study Design and Sampling Procedure

Hence the students are in the different department, sampling procedure that we used for the study is stratified sampling procedure stratified sampling technique is the probability which involves the division of the stratification of population by portioning the sample frame in to non-over capping and relatively homogenous group called strata

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3.4 Sample Size Determination

The sample size determination formula that we used for this study is as follow:

no=(1.96)2 (0.5x0.5) =150.0625

no = (z α/ ) 2 p q ( 0.08)2

n=no/(1+no/N) n=150.0625/(1+150.0625/429)=111.17421112

p=population proportion=0.5(from previous study)

q = 1-P = 0.5

d = 0.08 (margin error)

z = Normality distribution

α = level of significance (0.05)

Z0.25 = 1.96

We used proportional allocation to allocate the sample in each stratum

nh=Nhn/N

Total number of female students in each

3.5 Methods of Data Analysis

For analyzing data we used descriptive statistics and inferential statistics Descriptive statistics is the most famous for describing the characteristics of the sample and major study variable through frequency distribution and consists of method of organizing, displaying and describing the characteristics of the sample and major study unviable through frequency distribution and consists of method of organizing displaying and describing data by tables, graphs and summary measurement for the study we used histogram and frequency table to describe the achievement

of female students Inferential statistics is used to draw inferences about population from which the sample is selected Some inferential statistics that we used for the study are multiple linear regression and correlation Analysis

3.5.1 Variable Identification

Dependent variable: cumulative grade point average (CGPA)

Independent Variable:

- Study time

- Joining of department

- Use of stimulant for study

- Pocket money

- Boy friend influence

- Class missing per month

- Role of affirmative action

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3.5.2 Statistical Model Identification

Multiple Linear Regressions

The primary objective of regression is to develop a regression model, to explain the relation between one or more variables in a given population A particular form of regression model depends on the nature of the problem under study and the type of data variables Multiple linear regressions contain two or more independent variables and one dependent variable

The general form of a multiple linear regression model is given by:

Y = βo + β X + βX … βkXk + € i1 1 2

I = 1…n where βo is the intercept and β1, β2 … βk are coefficient of the Variables X …… Xk 1

Constant (βo) is the value of dependent variable (Y) when the all independent variables (Xi) are zero

β1 is the change in dependent variables (Y) when the independent variable (X ) increases1

by one, keeping other independent variables constant

βk is the change in dependent variable (Y) when the independent variable (Xk) increases

by one keeping other independent variables constant

Chi-square test of independence

Chi-square test is one of the most appropriate ways to use with categorical variables; it is non parameter test method (distribution free) It is uses to determine the significant association between the two variables it used to test the hypothesis test that the row and column variable are independent or not Chi-square is also a function of its degree of freedom The test statistics

is given by

= ~ ((r-1) (c-1))

Where: - E is the expected frequency corresponding to (i, j)IJ- th

O is observed frequencyIJ-

Degree of freedom

r- Number of rows

c- Number of columns

The test statistics has (r-1) (c-1) degree of freedom and α level of significance

Decision rule: reject H if the calculated value is greater than the tabulated value (the 0

significance level α=0.05) or reject H if p-value is less than α = 0.05.0

Chi-square use for different purpose among those the most important are the following -To test independency

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CORRELATION ANALYSIS

r =

1 perfect positive correlation between the two variables also when the value of r=0 there is no correlation The range of r is from -1 to 1 if r=-1 perfect negative correlation between the two variables and between the two variable When the value of r close to negative one it implies that inverse correlation , if it is close to 1 implies that positively correlated and when is close to zero implies that no correlation between the two variables

3.5.3 Assumption of the identified model

3.5.3.1 Assumption of multiple linear regression models

Dependent variable required to continuous

The relationship between dependent variable and independent variable is linear Explanatory variables are independent (no multicollinerity)

Error terms are uncorrected (no Autocorrelation

Error term has mean zero and constant variance (homoscedasticity)

Explanatory variables and error terms are independent

Assumption of chi-square

All individual observation in the sample should be independent

Sample must be drawn from the population interest

Each cell and every individual objective is independent of each other

Each number qualifies for one and only one cell in the table

It required sufficiently large expected frequency for each cell

Model adequacy checking:- :- the model adequacy checking is a way of checking whether the assumption of multiple linear regression is meeting or not

the residual analysis measures of variability of dependent variable that left un explained by regression model any departures from the assumption on the error term show up the residuals it analysis effective through plotting

Plot of residuals Normal probability plotting: to check the assumption of normality residual against fitted to check constant variance(Homoscedicity)

residuals versus time sequences :ton check the assumption of errors un correlated histogram to check the error have mean zero(Montgomery)

i) Linearity

There is a linear relationship between dependent and independent variables are called linearity assumption we will check by p-p plot

ii) Homoscedasticity: Error terms have constant variance points in the graph are dispersed at random fashion have no any trend; this indicates that he assumption of Homoscedisticity hold iii) Normality of Error Term:- the Error terms are normally distributed with mean zero and variance - can be tested by plotting residuals against the commutative probability

iv) Auto Correction:- the Error terms should be independent There is no relation between successive error terms Durbin Watson test is used to test Auto correlation

v) Multicolinearity: multicolinearity refers to the existence of high (perfect) linear relationship among repressors It can be tested by using VIF (variance Inflation factor)

given by:

VIF = 1/1-Ri where Ri is coefficient of determination that we will obtain from Xi on the2 2

other explanation variance

If the value of VIF less than 10 then there is no multicolinearity in the data

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Tentative Work Plan